The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Propagating annotations of molecular networks using in silico fragmentation
Open accessAbstract
The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., Fan, T. W.-M., Fiehn, O., Goodacre, R., Griffin, J. L., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0082-2 · Cited by 5,368
Wang, M., Carver, J. J., Phelan, V. V., Sanchez, L. M., Garg, N., Peng, Y., Nguyen, D. D., Watrous, J., Kapono, C. A., Luzzatto-Knaan, T., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3597 · Cited by 4,629
Self-citationHMDB 3.0—The Human Metabolome Database in 2013
Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., Djoumbou, Y., Mandal, R., Aziat, F., Dong, E., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1065 · Cited by 2,845
METLIN—a metabolite mass spectral database
Smith, C. A., Maille, G. O., Want, E. J., Qin, C., Trauger, S. A., Brandon, T. R., Custodio, D. E., Abagyan, R., & Siuzdak, G. (2005) · Therapeutic Drug Monitoring · doi:10.1097/01.ftd.0000179845.53213.39 · Cited by 2,226
Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
Langfelder, P., Zhang, B., & Horvath, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btm563 · Cited by 1,892
ClassyFire: automated chemical classification with a comprehensive, computable taxonomy
Djoumbou Feunang, Y., Eisner, R., Knox, C., Chepelev, L., Hastings, J., Owen, G., Fahy, E., Steinbeck, C., Subramanian, S., Bolton, E., et al. (2016) · Journal of Cheminformatics · doi:10.1186/s13321-016-0174-y · Cited by 1,525
LMSD: LIPID MAPS structure database
Sud, M., Fahy, E., Cotter, D., Brown, A., Dennis, E. A., Glass, C. K., Merrill, A. H., Murphy, R. C., Raetz, C. R. H., Russell, D. W., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl838 · Cited by 1,375
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Dührkop, K., Shen, H., Meusel, M., Rousu, J., & Böcker, S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509788112 · Cited by 1,190
MetFrag relaunched: incorporating strategies beyond in silico fragmentation
Ruttkies, C., Schymanski, E. L., Wolf, S., Hollender, J., & Neumann, S. (2016) · Journal of Cheminformatics · doi:10.1186/s13321-016-0115-9 · Cited by 1,052
Cited by
Feature-based molecular networking in the GNPS analysis environment
Nothias, L.-F., Petras, D., Schmid, R., Dührkop, K., Rainer, J., Sarvepalli, A., Protsyuk, I., Ernst, M., Tsugawa, H., Fleischauer, M., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0933-6 · Cited by 1,634
Self-citationSystematic classification of unknown metabolites using high-resolution fragmentation mass spectra
Dührkop, K., Nothias, L.-F., Fleischauer, M., Reher, R., Ludwig, M., Hoffmann, M. A., Petras, D., Gerwick, W. H., Rousu, J., Dorrestein, P. C., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0740-8 · Cited by 860
Self-citationHigh-confidence structural annotation of metabolites absent from spectral libraries
Hoffmann, M. A., Nothias, L.-F., Ludwig, M., Fleischauer, M., Gentry, E. C., Witting, M., Dorrestein, P. C., Dührkop, K., & Böcker, S. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01045-9 · Cited by 388
Self-citationZhou, Z., Luo, M., Zhang, H., Yin, Y., Cai, Y., & Zhu, Z.-J. (2022) · Nature Communications · doi:10.1038/s41467-022-34537-6 · Cited by 339
Wolfender, J.-L., Nuzillard, J.-M., van der Hooft, J. J. J., Renault, J.-H., & Bertrand, S. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b05112 · Cited by 305
Self-citation
Metadata
- Authors
- da Silva, R. R., Wang, M., Nothias, L.-F., van der Hooft, J. J. J., Caraballo-Rodríguez, A. M., Fox, E., Balunas, M. J., Klassen, J. L., Lopes, N. P., & Dorrestein, P. C.
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-04-18
- Volume
- 14
- Issue
- 4
- Pages
- e1006089
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W2800712778
- Cited by
- 363
- References
- 63
- FWCI
- 10.04
- Type
- journal article
- Language
- en
- Open access
- gold
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Propagating annotations of molecular networks using in silico fragmentation. https://app.cochat.ai/papers/10.1371/journal.pcbi.1006089
- The paper
- da Silva, R. R., Wang, M., Nothias, L.-F., van der Hooft, J. J. J., Caraballo-Rodríguez, A. M., Fox, E., Balunas, M. J., Klassen, J. L., Lopes, N. P., & Dorrestein, P. C. (2018). Propagating annotations of molecular networks using in silico fragmentation. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1006089
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
