The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index; 5 of the 28 sources its claims cite were checked for support.
A Whole-Cell Computational Model Predicts Phenotype from Genotype
Open accessAbstract
SUMMARY Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication rates. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.
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Claims the paper makes
38 Own result · 19 Own interpretation · 12 No full text of the sources · 11 No basis given · 5 Own method · 3 Supported so far · 2 Sources not found · 1 Supported · 1 Not checked yet
Every source the paper cites for this claim was checked and supports it.
In the paper
“Consistent with a recent experimental study by Vora et al., 2009, the predicted high-occupancy RNA polymerase regions correspond to highly transcribed rRNAs and tRNAs.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
What the sources say
- Supportedcites Vora et al., 2009 source
In Results, under “Discovery of Extended Protein Occupancy Domains (EPODs)” (page unavailable), Vora et al. report that highly expressed domains have extremely high RNA polymerase occupancy and are enriched for tRNAs. The same section links these domains to highly expressed genes including ribosomal RNAs. This supports the cited experimental correspondence; the prediction itself belongs to the citing paper. (LLM, conf=0.86)
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- Supported
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In the paper
“These results support the assertion that large-scale modeling can be used to support biological discovery (Kitano, 2002; Brenner, 2010).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
- Not checked — no full text of the sourcecites Kitano, 2002 source
- Supportedcites Brenner, 2010 source
The concluding passage in “Sequences and consequences” (page unavailable) proposes Cellmap as a computational model that, when complete, would allow researchers to formulate and test biological hypotheses. This supports the cited assertion that modeling can aid biological discovery, although Brenner distinguishes his proposed approach from inferring models directly from large datasets. (LLM, conf=0.88)
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In the paper
“We found that the model calculations were consistent with the observed doubling time (Figure 2A and 2B), cellular chemical composition (Figure 2C), replication of major cell mass fractions (Figure 2D), and gene expression (R2 = 0.68; Figure S1A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
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In the paper
“We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
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- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
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In the paper
“including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication rates.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
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In the paper
“We found that the model calculations were consistent with the observed doubling time (Figure 2A and 2B), cellular chemical composition (Figure 2C), replication of major cell mass fractions (Figure 2D), and gene expression (R2 = 0.68; Figure S1A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
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In the paper
“Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
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In the paper
“the experimentally measured DNA content per cell (Morowitz et al., 1962; Morowitz, 1992) represents less than one third of the calculated mass of the mycoplasma chromosome.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
What the sources say
- Not checked — no full text of the sourcecites Morowitz et al., 1962 source
- Not matchedcites Morowitz, 1992
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“We found that the model calculations were consistent with the observed doubling time (Figure 2A and 2B), cellular chemical composition (Figure 2C), replication of major cell mass fractions (Figure 2D), and gene expression (R2 = 0.68; Figure S1A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
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In the paper
“We found that the model calculations were consistent with the observed doubling time (Figure 2A and 2B), cellular chemical composition (Figure 2C), replication of major cell mass fractions (Figure 2D), and gene expression (R2 = 0.68; Figure S1A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
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In the paper
“Accordingly, the duration of the replication phase in individual cells is more closely related to the free dNTP content at the start of replication than to the dNTP content at the start of the cell cycle (Figure 4D).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
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In the paper
“Four gene disruption strains exhibited growth rates that were quantitatively different than those predicted by the model (Figure 7A)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“A third class of lethal gene disruptions impaired cell cycle processes. For these, the model predicted normal growth rates and metabolism, but incapacity to complete the cell cycle.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
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In the paper
“Our model suggests that to reproduce the observed growth rate in the absence of lpdA, the hypothetical Nox-dependent reaction would require a kcat of approximately 50 s−1 (Figure 7E), which represents only approximately 5% of the maximum throughput of this enzyme.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“Notably, the overall usage of ATP and GTP did not vary considerably in all but the very slowest of our simulations (Figure 5B)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Global distribution of energy
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In the paper
“Further categorization of the predicted collisions by chromosomal location indicates that the flux of protein-protein collisions correlates strongly with DNA-bound protein density (Figure 3F)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
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In the paper
“We found that there was relatively more cell-to-cell variation in the durations of the replication initiation (64.3%) and replication (38.5%) stages than in cytokinesis (4.4%) or the overall cell cycle (9.4%; Figure 4A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
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In the paper
“Significantly, these newly predicted kcat values are consistent with previously reported values.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“We then considered the processes that use ATP and GTP, and found that usage is dominated by production of mRNA and protein (Figure 5C).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Global distribution of energy
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In the paper
“The model accounts for previously observed gene essentiality with 79% accuracy (P < 10−7; Glass et al., 2006; Figure 6A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
What the sources say
- Not checked — no full text of the sourcecites Glass et al., 2006 source
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In the paper
“The mRNA and protein level distributions predicted by our model are also consistent with recently reported single-cell measurements (Figure 2H, compare to Taniguichi et al., 2010).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
What the sources say
- Not matchedcites Taniguichi et al., 2010
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Specifically, the duration of the initiation and replication phases are inversely related to each other in single cells (Figure 4E), such that longer initiation times led to shorter replication times.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
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In the paper
“The next most debilitating gene disruptions impacted the synthesis of a specific cell mass component such as RNA or protein. Interestingly, in these cases the model predicted an initial phase of near-normal growth followed by decreasing growth due to diminishing protein content.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
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In the paper
“As shown in Figure 6B, the non-viable strains were unable to adequately perform one or more of these major functions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
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In the paper
“We found a correlation (R2 = 0.49) between the predicted duration of replication initiation and the initial number of free DnaA monomers (Figure 4C)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
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In the paper
“In some cases (Figure 6B, fifth column), the time required for the levels of specific proteins to fall to lethal levels was greater than one generation (Figure 6C and 6D).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
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In the paper
“However, we did not detect growth using our colorimetric assay (Figure 7B), a discrepancy that warranted further investigation.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“We identified a Pdp kcat range for which the wild type and deoD gene disruption strains produce the same growth rate (Figure 7G).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“Our model also predicts “burst-like” protein synthesis due to the local effect of intermittent mRNA expression and the global effect of stochastic protein degradation on the availability of free amino acids for translation, comparable to recent reports by Yu et al., 2006 and So et al., 2011 (Figure 2G).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
What the sources say
- Not matchedcites Yu et al., 2006
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites So et al., 2011
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In the paper
“the model predicts that the flux through glycolysis is >100-fold more than that through the pentose phosphate and lipid biosynthesis pathways (Figure 2E).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
What the sources say
- Not checked — no full text of the sourcecites Yus et al., 2009 source
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In the paper
“RNA polymerase contributes the most to chromosomal exploration, binding 90% of the chromosome within the first 49 min of the cell cycle.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
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In the paper
“we investigated the synthesis dynamics of the high energy intermediates ATP, GTP, FAD(H2), NAD(H), and NADP(H), and found that ATP and GTP are synthesized at rates over 1,000-fold higher than the others (Figure 5A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Global distribution of energy
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In the paper
“An alternative method to determine the doubling time yielded a value that was 40% lower than the wild type (Table S1).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“Only a small range of the kcat values both reduced the thyA strain growth rate to the experimentally observed levels and was also consistent with the wild type growth rate.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“We found that two-thirds of the predictions were consistent with the measured growth rates.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“We found that the Nox sequence was far more similar to the LpdA sequence than any other gene product in the genome, with 61% coverage, 25% identity, and an expectation value less than 10−6 (Figure 7C).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
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In the paper
“We also found a large (44%) discrepancy between total energy usage and production (Figure 5D).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Global distribution of energy
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In the paper
“Instead, the model predicts that DNA replication proceeds at two distinct rates during the cell cycle.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
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In the paper
“The remaining lethal gene disruption strains grew so slowly compared to wild type that they were considered non-viable (Figure 6B, Figure S2).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“As a result, much of the data used to build and validate the model was obtained from other organisms.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
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- Rests on an assumption: Data and parameters obtained from other organisms are applicable enough to M. genitalium to build and validate the model.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The second limiting factor has been that no single computational method is sufficient to explain complex phenotypes in terms of molecular components and their interactions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
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In the paper
“Once the model was implemented and all parameters reconciled, we verified that the model recapitulates key features of our training data.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“The first approaches to modeling cellular physiology, based on ordinary differential equations (ODEs) (Atlas et al., 2008; Browning et al., 2004; Castellanos et al., 2004; Castellanos et al., 2007; Domach et al., 1984; Tomita et al., 1999), were limited by the difficulty in obtaining the necessary model parameters.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > Abstract
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Next, we validated the model against a broad range of independent datasets that were not used to construct the model and which encompass multiple biological functions – metabolomics, transcriptomics, and proteomics – and scales, from single cells to populations.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
In the paper
“The lpdA gene was originally determined to be non-essential (Glass et al., 2006).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
- Not checked — no full text of the sourcecites Glass et al., 2006 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This interplay buffers against the high variability in the duration of replication initiation, giving rise to substantially less variability in the length of the cell cycle.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We conclude that the model can be used to classify cellular phenotypes by their underlying molecular interactions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We therefore concluded that substrate promiscuity of Nox is likely to enable the lpdA disruption strain to survive.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“replication initiation occurs as DnaA protein monomers bind or unbind stochastically and cooperatively to form a multimeric complex at the replication origin (Figure 4B, top) (Browning et al., 2004).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
What the sources say
- Not checked — no full text of the sourcecites Browning et al., 2004 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Others have noted an uncoupling between catabolism and anabolism, attributing the difference to factors such as varying maintenance costs or energy spilling via futile cycles (Russell et al., 1995), and the model’s prediction estimates the total energy cost of such uncoupling.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Global distribution of energy
What the sources say
- Not checked — no full text of the sourcecites Russell et al., 1995 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“Furthermore, the nox gene product, NADH oxidase, has been shown to oxidize NAD (Schmidt et al., 1986).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
- Not checked — no full text of the sourcecites Schmidt et al., 1986 source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“however, the somewhat low correlation indicated that the duration depends on more than the initial conditions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The viability of the lpdA disruption strain suggests that this reaction could be catalyzed by another enzyme with a lower catalytic efficiency.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
hedgedconditionalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The whole-cell model therefore presents a novel hypothesis of an emergent control of cell-cycle duration that is independent of genetic regulation.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our model accurately recapitulates a broad set of experimental data, provides insight into several biological processes for which experimental assessment is not readily feasible, and enables the rapid identification of novel gene functions as well as specific cellular parameters.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our model accurately recapitulates a broad set of experimental data, provides insight into several biological processes for which experimental assessment is not readily feasible, and enables the rapid identification of novel gene functions as well as specific cellular parameters.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This indicates that the variability in replication initiation duration depends not only on variability in initial conditions, but also in the simulation itself.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Taking all of these specific tests of the model's predictions together, we concluded that our model recapitulates experimental data across multiple biological functions and scales.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
- Probably not a substantial claim. 7
- It may state two separate claims as one. 26
- Borderline: one of the tests for a substantial claim is unclear. 1
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Subsequently, alternative approaches were developed that require fewer parameters, including Boolean network modeling (Davidson et al., 2002) and constraint-based modeling (Orth et al., 2010; Thiele et al., 2009).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
What the sources say
- Not checked — no full text of the sourcecites Davidson et al., 2002 source
- Supportedcites Orth et al., 2010 source
The Orth et al. citation is attached to constraint-based modeling, not Boolean network modeling. In “Flux balance analysis is based on constraints,” the paper contrasts FBA with models requiring many difficult-to-measure kinetic parameters; “From constraints to optimizing a phenotype” states that FBA requires no kinetic parameters. (LLM, conf=0.93)
- Supportedcites Thiele et al., 2009 source
The Introduction states that, unlike traditional approaches, constraint-based modeling requires few, if any, parameters. Thiele et al. is cited for constraint-based modeling in the sentence; the separate Boolean-network citation is to Davidson et al. (LLM, conf=0.93)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“the predicted metabolite concentrations are within an order of magnitude of concentrations measured in Escherichia coli for 100% of the metabolites in one compilation of data (Sundararaj et al., 2004) and for 70% in a more recent high-throughput study (Bennett et al., 2009; Figure 2F).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model validation against independent experimental data
What the sources say
- Not checked — no full text of the sourcecites Sundararaj et al., 2004 source
- Supportedcites Bennett et al., 2009 source
The Results section (“Composition of the core E. coli metabolome”) reports absolute concentrations for 103 metabolites, confirming that Bennett et al. is the cited high-throughput E. coli measurement dataset. The 70% comparison with predicted concentrations is the citing paper’s own analysis (Figure 2F), not a result attributed to Bennett et al. (LLM, conf=0.90)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Our model predicts that over 30,000 collisions occur on average per cell cycle, leading to the displacement of 0.93 proteins per second.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
direct- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
Borderline substantial claim. It is unclear whether the paper’s conclusions depend on it. It is unclear why the paper says it holds. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The most debilitating disruptions involved metabolic genes and resulted in the inability to produce any of the major cell mass components.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Determining the molecular pathologies of single-gene disruption phenotypes
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the majority of collisions are caused by RNA polymerase (84%) and DNA polymerase (8%), most commonly resulting in the displacement of Structural Maintenance of Chromosome (SMC) proteins (70%), or single-stranded binding proteins (6%) (Figure 3E and Table S2F).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The model further predicts that the chromosome is explored very rapidly, with 50% of the chromosome having been bound by at least one protein within the first 6 min of the cell cycle, and 90% within the first 20 min (Figure 3B).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Reducing the Tdk kcat in the model did indeed reduce the predicted growth rate of the thyA strain, but it also affected the wild type growth rate (Figure 7F).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we experimentally measured the growth rates of twelve single-gene disruption strains – ten of which were correctly predicted to be viable and two of which that were incorrectly predicted to be nonviable – for comparison to our models' predictions (Figure 7A).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we observed that the stochastic aspect of the transcription and translation sub-models creates variability in the number of new DnaA monomers produced over time, as well as the DnaA binding and unbinding events themselves.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, the predicted DNA polymerase chromosomal occupancy is significantly lower and biased toward the terC (see below for further discussion).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For Tdk and Pdp, these values corresponded to distantly related organisms; however, the newly predicted kcat values are consistent with reports from more closely related species (Figure 7H).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“On average, this results in expression of 90% of genes within the first 143 min (Figure 3C), with transcription lagging RNA polymerase exploration due to the significant contribution of non-specific RNA polymerase-DNA interactions to RNA polymerase diffusion (Harada et al., 1999).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
What the sources say
- Not checked — no full text of the sourcecites Harada et al., 1999 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The whole-cell model was based on a detailed reconstruction of M. genitalium developed from over 900 primary sources, reviews, books, and databases.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > EXPERIMENTAL PROCEDURES > Reconstruction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Our model is based on a synthesis of over 900 publications and includes more than 1,900 experimentally observed parameters.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model training and parameter reconciliation
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, the underlying assumptions of these methods do not apply to all cellular processes and conditions, and building a whole-cell model entirely based on either method is therefore impractical.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Here, we present a “whole-cell” model of the bacterium Mycoplasma genitalium, a human urogenital parasite whose genome contains 525 genes (Fraser et al., 1995).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
What the sources say
- Not checked — no full text of the sourcecites Fraser et al., 1995 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“First, until recently not enough has been known about the individual molecules and their interactions to completely model any one organism.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > INTRODUCTION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In each of these three cases (lpdA, deoD, thyA), identifying a discrepancy between model predictions and experimental measurements led to further analysis which resolved the discrepancy, and also provided novel insight into M. genitalium biology (Figure 7I).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plaindirectn = 3- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The thyA gene product catalyzes dTMP production and can be complemented by the tdk gene product.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“The lpdA gene product is part of the pyruvate dehydrogenase complex, which catalyzes the transfer of electrons to NAD as a subset of the overall pyruvate dehydrogenase chemical reaction (de Kok et al., 1998).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
- Not checked — no full text of the sourcecites de Kok et al., 1998 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Initially replication proceeds quickly, due to the free dNTP content in the cell (Figure 4B, bottom). When DNA polymerase initially binds to the replication origin, dNTPs are abundant and replication can proceed unimpeded. When the dNTP pool is exhausted, however, the rate of replication slows to the rate of dNTP synthesis.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“DeoD catalyzes the conversion of deoxyadenosine to adenine and D-ribose-1-phosphate; these products can also be produced by the pdp gene product from deoxyuridine.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the whole-cell model can predict both the instantaneous protein chromosomal occupancy as well as the temporal dynamics and interactions of every DNA-binding protein at the genomic scale at single-cell resolution.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Prediction of DNA binding protein interactions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Moreover, the nox locus falls in a sub-operon that contains two other pyruvate dehydrogenase genes and has been shown to be coexpressed with pdhA (Guell et al., 2009) (Figure 7D)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
- Not checked — no full text of the sourcecites Guell et al., 2009 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Since previous studies have shown that many M. genitalium genes are multi-functional (Pollack et al., 2002; Cordwell et al., 1997)”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Taken together, the data suggested that disrupting the lpdA gene had a severe, but non-critical impact on cell growth.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This occurs because cells that require extra time to initiate replication also build up a large dNTP surplus, leading to faster replication.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Identification of metabolism as an emergent cell cycle regulator
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We have developed a comprehensive, whole-cell model that accounts for all of the annotated gene functions identified in M. genitalium and explains a variety of emergent behaviors in terms of molecular interactions.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Resistance to most antibiotics, the lack of a chemically defined medium, and a cell size that requires advanced microscopy techniques for visualization, all greatly limit the range of experimental techniques available to study this organism.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our model accurately recapitulates a broad set of experimental data, provides insight into several biological processes for which experimental assessment is not readily feasible, and enables the rapid identification of novel gene functions as well as specific cellular parameters.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > DISCUSSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Biological systems are modular, so cells can be modeled by dividing them into functional processes, modeling each process independently on a short time scale, and integrating the sub-models at longer time scales.
“Because biological systems are modular, cells can be modeled by (1) dividing cells into functional processes, (2) independently modeling each process on a short time scale, and (3) integrating process sub-models at longer time scales.”
The authors state this as an assumption.
The cellular process sub-models are approximately independent of one another on short time scales of less than one second.
“We began with the assumption that the sub-models are approximately independent on short time scales (less than one second in this work).”
The paper relies on this without support.
Data and parameters obtained from other organisms are applicable enough to M. genitalium to build and validate the model.
“As a result, much of the data used to build and validate the model was obtained from other organisms.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Existing cell models are often rule-based and combine assumptions about the underlying biological mechanisms with parameters fit from observational data.”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Since this pioneering work, genome-wide models have been developed to represent other bacterial organisms, including Escherichia coli.8,20–22”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The first whole-cell model was developed in 2012, representing all 482 genes and molecular functions known for an organism: the bacteria Mycobacterium genitalium.8”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Unfortunately, no one organism has a complete set of experimentally determined kinetic parameters, chemical composition, and physical characteristics, so the model we present here, as well as other whole-cell models, has depended on the transferability of quantities among related organisms.1”
From Bringing the genetically minimal cell to life on a computer in 4D (2026) · cites this paper as [3]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“They generally rely on explicitly defined mathematical or computational approaches, such as differential equations,7–9 stochastic simulations,10,11 or agent-based models.12,13”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [8]
The cited source says what the claim attributes to it.
In the citing paper
“there have been significant strides in computational modeling of cell states”
From Bringing the genetically minimal cell to life on a computer in 4D (2026) · cites this paper as [3]
In the citing paper
“The latter two approaches either are mostly qualitative in nature or require an excessive number of parameters that are not currently available.”
From Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints (2017) · cites this paper as Karr et al, 2012
In the citing paper
“recent research [10] clearly shows the feasibility of comprehensive large-scale whole-cell computational modelling.”
From Reverse engineering and identification in systems biology: strategies, perspectives and challenges (2014) · cites this paper as [10]
In the citing paper
“Recently it was also shown that yeast has a similar intrinsic sensing mechanism to balance growth and stress resistance [160,161].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [161]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
“An alternative method to determine the doubling time yielded a value that was 40% lower than the wild type (Table S1).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
“Taken together, the data suggested that disrupting the lpdA gene had a severe, but non-critical impact on cell growth.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
“We therefore hypothesized that by reducing the kcat value for Tdk in the model we would see a reduction in the growth rate of the tdk disruption strain.”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Model-driven biological discovery
“Reducing the Tdk kcat in the model did indeed reduce the predicted growth rate of the thyA strain, but it also affected the wild type growth rate (Figure 7F).”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > RESULTS > Whole-cell model construction and integration
“We began with the assumption that the sub-models are approximately independent on short time scales (less than one second in this work).”
§ A Whole-Cell Computational Model Predicts Phenotype from Genotype > EXPERIMENTAL PROCEDURES > Cellular Process Sub-models
“We divided M. genitalium into the 28 functional processes illustrated in Figure 1, and modeled each process independently on a 1 s time scale using different mathematics and different experimental data.”
Citations
Cites
Systems biology: a brief overview
Kitano, H. (2002) · Science · doi:10.1126/science.1069492 · Cited by 4,265 · cited 1×
“These results support the assertion that large-scale modeling can be used to guide biological discovery (Kitano, 2002; Brenner, 2010).”
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903 · cited 2×
“Subsequently, alternative approaches were developed that require fewer parameters, including Boolean network modeling (Davidson et al., 2002) and constraint-based modeling (Orth et al., 2010; Thiele et al., 2009).”
Creation of a Bacterial Cell Controlled by a Chemically Synthesized Genome
Gibson, D. G., Glass, J. I., Lartigue, C., Noskov, V. N., Chuang, R.-Y., Algire, M. A., Benders, G. A., Montague, M. G., Ma, L., Moodie, M. M., et al. (2010) · Science · doi:10.1126/science.1190719 · Cited by 2,638
Self-citationThe Minimal Gene Complement of Mycoplasma genitalium
Fraser, C. M., Gocayne, J. D., White, O., Adams, M. D., Clayton, R. A., Fleischmann, R. D., Bult, C. J., Kerlavage, A. R., Sutton, G., Kelley, J. M., et al. (1995) · Science · doi:10.1126/science.270.5235.397 · Cited by 2,545 · cited 2×
“Here, we present a ‘‘whole-cell’’ model of the bacterium Mycoplasma genitalium , a human urogenital parasite whose genome contains 525 genes (Fraser et al., 1995).”
Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells
Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S. (2010) · Science · doi:10.1126/science.1188308 · Cited by 1,982 · cited 2×
“We found that the model calculations were consistent with the observed doubling time (Figures 2A and 2B), cellular chemical composition (Figure 2C), replication of major cell mass fractions (Figure 2D), and gene expression ( R 2 = 0.68; Figure S1A).”
ResultInfluentialAbsolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli
Bennett, B. D., Kimball, E. H., Gao, M., Osterhout, R., Van Dien, S. J., & Rabinowitz, J. D. (2009) · Nature Chemical Biology · doi:10.1038/nchembio.186 · Cited by 1,830 · cited 3×
“(F) Ratios of observed (Sundararaj et al., 2004; Bennett et al., 2009) and average predicted concentrations of 39 metabolites.”
A genomic regulatory network for development
Davidson, E. H., Rast, J. P., Oliveri, P., Ransick, A., Calestani, C., Yuh, C.-H., Minokawa, T., Amore, G., Hinman, V., Arenas-Mena, C., et al. (2002) · Science · doi:10.1126/science.1069883 · Cited by 1,567 · cited 2×
“Subsequently, alternative approaches were developed that require fewer parameters, including Boolean network modeling (Davidson et al., 2002) and constraint-based modeling (Orth et al., 2010; Thiele et al., 2009).”
Complete Chemical Synthesis, Assembly, and Cloning of a Mycoplasma genitalium Genome
Gibson, D. G., Benders, G. A., Andrews-Pfannkoch, C., Denisova, E. A., Baden-Tillson, H., Zaveri, J., Stockwell, T. B., Brownley, A., Thomas, D. W., Algire, M. A., et al. (2008) · Science · doi:10.1126/science.1151721 · Cited by 1,243
Self-citationA comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011
Orth, J. D., Conrad, T. M., Na, J., Lerman, J. A., Nam, H., Feist, A. M., & Palsson, B. Ø. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.65 · Cited by 1,006 · cited 1×
“Models of biological processes have been increasing in complexity and scope (Covert et al., 2004; Orth et al., 2011; Thiele et al., 2009), but with efforts at increased inclusiveness of genes, parameters, and molecular functions come a number of challenges.”
Energetics of bacterial growth: balance of anabolic and catabolic reactions
Russell, J. B., & Cook, G. M. (1995) · Microbiological Reviews · doi:10.1128/mr.59.1.48-62.1995 · Cited by 927
Cited by
Sorted by citations
Bassett, D. S., & Sporns, O. (2017) · Nature Neuroscience · doi:10.1038/nn.4502 · Cited by 2,398
Design and synthesis of a minimal bacterial genome
Hutchison, C. A., Chuang, R.-Y., Noskov, V. N., Assad-Garcia, N., Deerinck, T. J., Ellisman, M. H., Gill, J., Kannan, K., Karas, B. J., Ma, L., et al. (2016) · Science · doi:10.1126/science.aad6253 · Cited by 1,500
Self-citationNext-Generation Machine Learning for Biological Networks
Camacho, D. M., Collins, K. M., Powers, R. K., Costello, J. C., & Collins, J. J. (2018) · Cell · doi:10.1016/j.cell.2018.05.015 · Cited by 1,011
The systemic immune response to trauma: an overview of pathophysiology and treatment
Lord, J. M., Midwinter, M. J., Chen, Y., Belli, A., Brohi, K., Kovacs, E. J., Koenderman, L., Kubes, P., & Lilford, R. J. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60687-5 · Cited by 887
Constraint-based models predict metabolic and associated cellular functions
Bordbar, A., Monk, J. M., King, Z. A., & Palsson, B. Ø. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3643 · Cited by 844
“Trends in current literature 89,91,96 indicate that other cellular processes may be modelled using alternative frameworks that are better suited for a particular biological phenomena.”
Background
Metadata
- Authors
- Karr, J. R., Sanghvi, J. C., Macklin, D. N., Gutschow, M. V., Jacobs, J. M., Bolival, B., Assad-Garcia, N., Glass, J. I., & Covert, M. W.
- Affiliations
- Stanford University (US)
- J. Craig Venter Institute (US)
- Corresponding author
- Covert, Markus W.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-07
- Volume
- 150
- Issue
- 2
- Pages
- 389-401
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3413483
- OpenAlex
- W2081781433
- Semantic Scholar
- 97d676e4cc348a078b766783a555de501b20191e
- Cited by
- 1,300
- References
- 47
- Citations by year
- 2026: 84 · 2025: 59 · 2024: 48 · 2023: 52 · 2022: 51 · 2021: 91 · 2020: 75 · 2019: 101 · 2018: 105 · 2017: 104 · 2016: 105 · 2015: 137 · 2014: 119 · 2013: 126 · 2012: 41
- FWCI
- 54.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 384 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (DP1OD006413)
- U.S. National Library of Medicine (DP1LM011510)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- Mycoplasma genitalium, genotype-phenotype correlation, life cycle modeling, DNA replication initiation, gene expression regulation, kinetic parameter estimation
- MeSH terms
- Bacterial Proteins, Cell Cycle, Computer Simulation, DNA-Binding Proteins, Models, Biological, Phenotype, Mycoplasma genitalium, Molecular Sequence Annotation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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