The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Efficiency of DNA replication in the polymerase chain reaction
Open accessAbstract
A detailed quantitative kinetic model for the polymerase chain reaction (PCR) is developed, which allows us to predict the probability of replication of a DNA molecule in terms of the physical parameters involved in the system. The important issue of the determination of the number of PCR cycles during which this probability can be considered to be a constant is solved within the framework of the model. New phenomena of multimodality and scaling behavior in the distribution of the number of molecules after a given number of PCR cycles are presented. The relevance of the model for quantitative PCR is discussed, and a novel quantitative PCR technique is proposed.
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.
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 cited source says what the claim attributes to it.
In the citing paper
“PCR is an exponential process, so small random variations early on in amplification can have a large impact on distribution18–24.”
From Quantifying Molecular Bias in DNA Data Storage (2019) · cites this paper as [19]
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
Molecular Cloning: A Laboratory Manual
Sambrook, J., Fritsch, E., & Maniatis, T. (1989) · UCLA - Biblioteca de Ciencias de la Salud · Cited by 133,589
Molecular cloning: A laboratory manual
Deininger, P. L. (1990) · Analytical Biochemistry · doi:10.1016/0003-2697(90)90595-z · Cited by 84,684
An introduction to probability theory and its applications
(1958) · Journal of the Franklin Institute · doi:10.1016/0016-0032(58)90688-4 · Cited by 29,621
Stochastic Processes in Physics and Chemistry
(2007) · Elsevier eBooks · doi:10.1016/b978-0-444-52965-7.x5000-4 · Cited by 9,096
An Introduction to Probability Theory and Its Applications.
Bharucha-Reid, A. T., & Feller, W. (1967) · American Mathematical Monthly · doi:10.2307/2314609 · Cited by 6,365
[21] Specific synthesis of DNA in vitro via a polymerase-catalyzed chain reaction
Mullis, K. B., & Faloona, F. (1987) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/0076-6879(87)55023-6 · Cited by 5,762
Molecular Computation of Solutions to Combinatorial Problems
Adleman, L. M. (1994) · Science · doi:10.1126/science.7973651 · Cited by 4,474
The Theory of Branching Processes
Ney, P. E., & Harris, T. E. (1965) · Technometrics · doi:10.2307/1266137 · Cited by 2,442
The Theory of Branching Processes
Harris, T. E. (1963) · Springer eBooks · doi:10.1007/978-3-642-51866-9 · Cited by 2,107
Athreya, K. B., & Ney, P. E. (1972) · Springer eBooks · doi:10.1007/978-3-642-65371-1 · Cited by 1,756
Research works printed but not linked: 3
- , eds R Gestland, J Atkins (Cold Spring Harbor Lab. Press, Plainview, NY The RNA World, 1993).
- P Kaplan, G Cecchi, A Libchaber Proceedings of the 2nd Annual Princeton Conference on DNA-Based Computation, eds E Baum, D Boneh, P Kaplan, J Reif, A Seeman (Am. Mathematical Soc., Providence, RI, in press. (1996).
- 10.1021/bi00399a057 · DOI
Cited by
Sorted by citations
Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data
Ruijter, J. M., Ramakers, C., Hoogaars, W. M. H., Karlen, Y., Bakker, O., van den Hoff, M. J. B., & Moorman, A. F. M. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp045 · Cited by 3,043
Svec, D., Tichopad, A., Novosadova, V., Pfaffl, M. W., & Kubista, M. (2015) · Biomolecular Detection and Quantification · doi:10.1016/j.bdq.2015.01.005 · Cited by 601
Statistical significance of quantitative PCR
Karlen, Y., McNair, A., Perseguers, S., Mazza, C., & Mermod, N. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-131 · Cited by 373
Sources of PCR-induced distortions in high-throughput sequencing data sets
Kebschull, J. M., & Zador, A. M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv717 · Cited by 300
Robust Quantification of Polymerase Chain Reactions Using Global Fitting
Carr, A. C., & Moore, S. D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037640 · Cited by 303
Ruijter, J. M., Pfaffl, M. W., Zhao, S., Spiess, A., Boggy, G. J., Blom, J., Rutledge, R. G., Sisti, D., Lievens, A., Preter, K. D., et al. (2012) · Methods · doi:10.1016/j.ymeth.2012.08.011 · Cited by 258
Felske, A., Akkermans, A. D. L., & de Vos, W. M. (1998) · Applied and Environmental Microbiology · doi:10.1128/aem.64.11.4581-4587.1998 · Cited by 233
Validating TrueAllele ® DNA Mixture Interpretation* ,†
Perlin, M. W., Legler, M. M., Spencer, C. E., Smith, J. L., Allan, W. P., Belrose, J. L., & Duceman, B. W. (2011) · Journal of Forensic Sciences · doi:10.1111/j.1556-4029.2011.01859.x · Cited by 228
Gill, P. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki205 · Cited by 137
Analysis of Forensic DNA Mixtures with Artefacts
Cowell, R. G., Graversen, T., Lauritzen, S. L., & Mortera, J. (2014) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/rssc.12071 · Cited by 132
Bustin, S., & Nolan, T. (2017) · European Journal of Clinical Investigation · doi:10.1111/eci.12801 · Cited by 113
Quantifying Molecular Bias in DNA Data Storage
Chen, Y.-J., Takahashi, C. N., Organick, L., Stewart, K., Ang, S. D., Weiss, P., Peck, B., Seelig, G., Ceze, L., & Strauss, K. (2019) · doi:10.1101/566554 · Cited by 116
A New Method for Quantitative Real-Time Polymerase Chain Reaction Data Analysis
Rao, X., Lai, D., & Huang, X. (2013) · Journal of Computational Biology · doi:10.1089/cmb.2012.0279 · Cited by 107
Best, K., Oakes, T., Heather, J., Shawe-Taylor, J. S., & Chain, B. (2015) · Scientific Reports · doi:10.1038/srep14629 · Cited by 103
Christopoulos, T. K. (1999) · Analytical Chemistry · doi:10.1021/a19900161 · Cited by 95
An Information Gap in DNA Evidence Interpretation
Perlin, M. W., & Sinelnikov, A. (2009) · PLoS ONE · doi:10.1371/journal.pone.0008327 · Cited by 71
Evaluation of loss of heterozygosity/allelic imbalance scoring in tumor DNA
Skotheim, R. I., Diep, C. B., Kraggerud, S. M., Jakobsen, K. S., & Lothe, R. A. (2001) · Cancer Genetics and Cytogenetics · doi:10.1016/s0165-4608(00)00433-7 · Cited by 71
Validation of kinetics similarity in qPCR
Bar, T., Kubista, M., & Tichopád, A. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr778 · Cited by 60
Alveolar macrophage dynamics in murine lung regeneration
Chamoto, K., Gibney, B. C., Ackermann, M., Lee, G. S., Lin, M., Konerding, M. A., Tsuda, A., & Mentzer, S. J. (2011) · Journal of Cellular Physiology · doi:10.1002/jcp.24009 · Cited by 55
A kinetic model of quantitative real‐time polymerase chain reaction
Mehra, S., & Hu, W. (2005) · Biotechnology and Bioengineering · doi:10.1002/bit.20555 · Cited by 51
White, J. A., Kufera, J. T., Bachmann, N., Dai, W., Simonetti, F. R., Armstrong, C., Lai, J., Beg, S. A., Siliciano, J. D., & Siliciano, R. F. (2022) · PLoS Pathogens · doi:10.1371/journal.ppat.1010845 · Cited by 48
Mátyás, G., Giunta, C., Steinmann, B. U., Hossle, J. P., & Hellwig, R. (2001) · Human Mutation · doi:10.1002/humu.10013 · Cited by 48
Evaluation of SYBR Green real time PCR for detecting SARS-CoV-2 from clinical samples
Pereira-Gómez, M., Fajardo, Á., Echeverría, N., Tort, L. F. L., Perbolianachis, P., Costábile, A., Aldunate, F., Moreno, P., & Moratorio, G. (2020) · Journal of Virological Methods · doi:10.1016/j.jviromet.2020.114035 · Cited by 49
Lalam, N., Jacob, C., & Jagers, P. (2004) · Advances in Applied Probability · doi:10.1239/aap/1086957587 · Cited by 46
Ballantyne, J., Hanson, E., & Perlin, M. W. (2012) · Science & Justice · doi:10.1016/j.scijus.2012.04.004 · Cited by 44
Estimation of the reaction efficiency in polymerase chain reaction
Lalam, N. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.06.001 · Cited by 41
Stochastic sampling effects in STR typing: Implications for analysis and interpretation
Timken, M. D., Klein, S. B., & Buoncristiani, M. R. (2014) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2014.03.015 · Cited by 42
Milanović, V., Osimani, A., Roncolini, A., Garofalo, C., Aquilanti, L., Pasquini, M., Tavoletti, S., Vignaroli, C., Canonico, L., Ciani, M., et al. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.03036 · Cited by 39
Efficiency of the polymerase chain reaction
Booth, C. S., Pienaar, E., TerMaat, J. R., Whitney, S. E., Louw, T. M., & Viljoen, H. J. (2010) · Chemical Engineering Science · doi:10.1016/j.ces.2010.05.046 · Cited by 45
So FAR: Software for Fully Automatic Evaluation of Real-Time PCR Data
Wilhelm, J., Pingoud, A. M., & Hahn, M. (2003) · BioTechniques · doi:10.2144/03342rr03 · Cited by 36
Validating TrueAllele® Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
Bauer, D. W., Butt, N. A., Hornyak, J. M., & Perlin, M. W. (2019) · Journal of Forensic Sciences · doi:10.1111/1556-4029.14204 · Cited by 34
Designer DNA biomolecules as a defined biomaterial for 3D bioprinting applications
Budharaju, H., Zennifer, A., Sethuraman, S., Paul, A., & Sundaramurthi, D. (2021) · Materials Horizons · doi:10.1039/d1mh01632f · Cited by 34
Perlin, M. W., Dormer, K., Hornyak, J. M., Schiermeier‐Wood, L., & Greenspoon, S. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0092837 · Cited by 33
Computational challenges in combinatorial library design for protein engineering
Moore, G. L., & Maranas, C. D. (2004) · AIChE Journal · doi:10.1002/aic.10025 · Cited by 34
Migration of CD11b+ accessory cells during murine lung regeneration
Chamoto, K., Gibney, B. C., Lee, G. S., Ackermann, M., Konerding, M. A., Tsuda, A., & Mentzer, S. J. (2013) · Stem Cell Research · doi:10.1016/j.scr.2012.12.006 · Cited by 31
Validation of an STR peak area model
Cowell, R. G. (2009) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2009.01.006 · Cited by 30
Hansson, O., Egeland, T., & Gill, P. (2016) · International Journal of Legal Medicine · doi:10.1007/s00414-016-1453-x · Cited by 29
Polymerase chain reaction in natural convection systems: A convection-diffusion-reaction model
Yariv, E., Ben-Dov, G., & Dorfman, K. D. (2005) · Europhysics Letters (EPL) · doi:10.1209/epl/i2005-10171-6 · Cited by 28
Angiogenesis gene expression in murine endothelial cells during post-pneumonectomy lung growth
Lin, M., Chamoto, K., Gibney, B. C., Lee, G. S., Simpson, D. C., Houdek, J. P., Konerding, M. A., Tsuda, A., & Mentzer, S. J. (2011) · Respiratory Research · doi:10.1186/1465-9921-12-98 · Cited by 26
Duffy, K. R., Gurram, N., Peters, K. C., Wellner, G. A., & Grgicak, C. M. (2016) · Electrophoresis · doi:10.1002/elps.201600385 · Cited by 25
Savonnet, M., Aubret, M., Laurent, P., Roupioz, Y., Cubizolles, M., & Buhot, A. (2022) · Biosensors · doi:10.3390/bios12050346 · Cited by 24
Elelu, N., Ferrolho, J., Couto, J., Domingos, A., & Eisler, M. C. (2016) · Experimental and Applied Acarology · doi:10.1007/s10493-016-0081-y · Cited by 22
Braun, P. R., Nguyen, M. D.-T., Walter, M. C., & Grass, G. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222212224 · Cited by 20
Kinetic characterisation of primer mismatches in allele-specific PCR: a quantitative assessment
Waterfall, C. M., Eisenthal, R., & Cobb, B. D. (2002) · Biochemical and Biophysical Research Communications · doi:10.1016/s0006-291x(02)02750-x · Cited by 20
Principles of rapid polymerase chain reactions: mathematical modeling and experimental verification
Whitney, S. E., Alugupally, S., Nelson, R. M., & Viljoen, H. J. (2004) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2004.03.001 · Cited by 20
Lamberton, P. H. L., Cheke, R., Walker, M., Winskill, P., Crainey, J. L., Boakye, D. A., Osei-Atweneboana, M. Y., Tirados, I., Wilson, M. D., Tetteh-Kumah, A., et al. (2016) · Parasites & Vectors · doi:10.1186/s13071-016-1703-2 · Cited by 19
Peng, X., & Dorman, K. S. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad002 · Cited by 17
Ligation-Based High-Performance Mimetic Enzyme Sensing Platform for Nucleic Acid Detection
Yan, X., Yang, P., Qiu, D., Chen, D., Pan, J., Zhang, X., Ju, H., & Zhou, J. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.3c04417 · Cited by 18
Simulation and real-time monitoring of polymerase chain reaction for its higher efficiency
Lee, J. Y., Lim, H., Yoo, S.-I., Zhang, B., & Park, T. H. (2005) · Biochemical Engineering Journal · doi:10.1016/j.bej.2005.02.023 · Cited by 19
Alveolar Epithelial Dynamics in Postpneumonectomy Lung Growth
Chamoto, K., Gibney, B. C., Ackermann, M., Lee, G. S., Konerding, M. A., Tsuda, A., & Mentzer, S. J. (2013) · The Anatomical Record · doi:10.1002/ar.22659 · Cited by 16
Polymerase Chain Reaction: A Markov Process Approach
Velikanov, M. V., & Kapral, R. (1999) · Journal of Theoretical Biology · doi:10.1006/jtbi.1999.1031 · Cited by 16
Real-time cdPCR opens a window into events occurring in the first few PCR amplification cycles
Duewer, D. L., Kline, M. C., & Romsos, E. L. (2015) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-015-9073-8 · Cited by 14
Kourkouli, A., Τhomaidis, Ν. S., Dasenaki, M. E., & Markou, A. N. (2024) · Molecules · doi:10.3390/molecules29081820 · Cited by 14
Figdor, D., & Brundin, M. (2016) · Journal of Endodontics · doi:10.1016/j.joen.2016.04.015 · Cited by 14
Weng, Z., Li, J., Wu, Y., Xiu, X., Wang, F., Zuo, X., Song, P., & Fan, C. (2025) · Nature Communications · doi:10.1038/s41467-025-55986-9 · Cited by 15
Sequence-Dependent Biophysical Modeling of DNA Amplification
Marimuthu, K., Jing, C., & Chakrabarti, R. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.08.019 · Cited by 13
Simulation of between Repeat Variability in Real Time PCR Reactions
Lievens, A., Aelst, S. V., den Bulcke, M. V., & Goetghebeur, E. J. T. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047112 · Cited by 11
Modeling bias and variation in the stochastic processes of small RNA sequencing
Argyropoulos, C., Etheridge, A., Sakhanenko, N. A., & Galas, D. J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx199 · Cited by 11
Felske, A., Pauling, B. V., von Canstein, H., Li, Y., Lauber, J., Buer, J., & Wagner‐Döbler, I. (2001) · BioTechniques · doi:10.2144/01301rr02 · Cited by 10
Perlin, M. W. (2015) · Journal of Pathology Informatics · doi:10.4103/2153-3539.168525 · Cited by 9
Elnaggar, J. H., Ardizzone, C. M., Cerca, N., Toh, E. C., Łaniewski, P., Lillis, R., Herbst‐Kralovetz, M. M., Quayle, A. J., Muzny, C. A., & Taylor, C. M. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1198113 · Cited by 9
Empirical insights into the stochasticity of small RNA sequencing
Qin, L., Tuschl, T., & Singer, S. (2016) · Scientific Reports · doi:10.1038/srep24061 · Cited by 8
Stimulation of voltage-dependent Ca2+channels by NO at rat myenteric neurons
Sitmo, M., Rehn, M., & Diener, M. (2007) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00124.2007 · Cited by 8
Emulsion PCR (ePCR) as a Tool to Improve the Power of DGGE Analysis for Microbial Population Studies
Iacumin, L., Cecchini, F., Vendrame, M., & Comi, G. (2020) · Microorganisms · doi:10.3390/microorganisms8081099 · Cited by 8
Emergence of fractals in aggregation with stochastic self-replication
Hassan, M. K., Hassan, M. Z., & Islam, N. (2013) · Physical Review E · doi:10.1103/physreve.88.042137 · Cited by 8
Milanović, V., Cardinali, F., Belleggia, L., Garofalo, C., Pasquini, M., Tavoletti, S., Riolo, P., Ruschioni, S., Isidoro, N., Osimani, A., et al. (2021) · Journal of Functional Foods · doi:10.1016/j.jff.2021.104490 · Cited by 7
Sueiro, R. A., Lamas, J., Palenzuela, O. R., Guliás, P., Díez‐Vives, C., García-Ulloa, A., & Leiro, J. M. (2022) · Aquaculture · doi:10.1016/j.aquaculture.2022.738303 · Cited by 6
Dynamics and control of DNA sequence amplification
Marimuthu, K., & Chakrabarti, R. (2014) · The Journal of Chemical Physics · doi:10.1063/1.4899053 · Cited by 6
Lalam, N., & Jacob, C. (2007) · Mathematical Population Studies · doi:10.1080/08898480701298418 · Cited by 5
Smith, S. E., Swan, E. R., & Furber, K. L. (2024) · Biochemistry and Cell Biology · doi:10.1139/bcb-2024-0088 · Cited by 4
Experimental validation of a fundamental model for PCR efficiency
Louw, T. M., Booth, C. S., Pienaar, E., TerMaat, J. R., Whitney, S. E., & Viljoen, H. J. (2011) · Chemical Engineering Science · doi:10.1016/j.ces.2011.01.029 · Cited by 8
Limits of Performance of Quantitative Polymerase Chain Reaction Systems
Vikalo, H., Hassibi, B., & Hassibi, A. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2037088 · Cited by 5
A quantitative approach for polymerase chain reactions based on a hidden Markov model
Lalam, N. (2008) · Journal of Mathematical Biology · doi:10.1007/s00285-008-0238-3 · Cited by 5
Huang, Y., Chen, X., Li, X., Shu, P., Wang, H., Hou, T., Wang, Y., Song, F., & Zhang, J. (2021) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2021.102609 · Cited by 5
Coagulation and self-duplication processes of a chain-shaped polymer system
Jian-Hong, K., Zheng, Y., Lin, Z., & Chen, X. (2007) · Physics Letters A · doi:10.1016/j.physleta.2007.03.087 · Cited by 4
Crissman, J. W., Lin, Y., Separa, K., Duquette, M., Cohen, M., Velasquez, C., & Cujec, T. P. (2020) · PLoS ONE · doi:10.1371/journal.pone.0241803 · Cited by 4
Validation and Estimation of Parameters for a General Probabilistic Model of the PCR Process
Saha, N., Watson, L. T., Kafadar, K., Ramakrishnan, N., Onufriev, A. V., Mane, S. P., & Vásquez-Robinet, C. (2007) · Journal of Computational Biology · doi:10.1089/cmb.2006.0123 · Cited by 4
Reducing Bias and Quantifying Uncertainty in Fluorescence Produced by PCR
DeJaco, R. F., Roberts, M. J., Romsos, E. L., Vallone, P. M., & Kearsley, A. J. (2023) · Bulletin of Mathematical Biology · doi:10.1007/s11538-023-01182-z · Cited by 3
Molecular quantification of genes encoding for green-fluorescent proteins
Felske, A., Vandieken, V., Pauling, B. V., von Canstein, H., & Wagner‐Döbler, I. (2003) · Journal of Microbiological Methods · doi:10.1016/s0167-7012(02)00184-7 · Cited by 3
ML Estimation of DNA Initial Copy Number in Polymerase Chain Reaction (PCR) Processes
Vikalo, H., Hassibi, B., & Hassibi, A. (2007) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2007.366705 · Cited by 3
A general probabilistic model of the PCR process
Saha, N., Watson, L. T., Kafadar, K., Onufriev, A. V., Ramakrishnan, N., Vásquez-Robinet, C., & Watkinson, J. I. (2006) · Applied Mathematics and Computation · doi:10.1016/j.amc.2006.01.092 · Cited by 3
Monitoring the Persistence of Pseudomonas sivasensis Strain CF10PS3 in Cereal Fields
Delitte, M., Dubois, B., Mahillon, J., Debode, F., & Bragard, C. (2024) · MicrobiologyOpen · doi:10.1002/mbo3.70005 · Cited by 2
A two stage model for quantitative PCRPreprint
Stone, E., Goldes, J., & Garlick, M. (2006) · arXiv (Cornell University) · doi:10.48550/arxiv.q-bio/0603004 · Cited by 2
Kinetics of catalytically activated duplication in aggregation growth
Haifeng, W., Zhen-Quan, L., Gao, Y. L., & Xu, C. (2009) · Chinese Physics B · doi:10.1088/1674-1056/18/8/074 · Cited by 2
On joint maximum-likelihood estimation of PCR efficiency and initial amount of target
Vikalo, H., Hassibi, B., & Hassibi, A. (2006) · IEEE International Workshop on Genomic Signal Processing and Statistics · doi:10.1109/gensips.2006.353149 · Cited by 2
Deep learning uncovers sequence-specific amplification bias in multi-template PCRPreprint
Gimpel, A. L., Fan, B., Chen, D., Wölfle, L. O. D., Horn, M., Meng-Papaxanthos, L., Antkowiak, P. L., Stark, W. J., Christen, B., Borgwardt, K. M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.20.614030 · Cited by 2
Salter, I., Brandner, M. M., Djurhuus, A., Præbel, K., & Wangensteen, O. S. (2026) · Environmental DNA · doi:10.1002/edn3.70253 · Cited by 1
The reliability and reporting of DNA match strength for uncertain genotype evidence
Perlin, M. W., Allan, W. P., Bracamontes, J. M., & Legler, M. M. (2026) · Heliyon · doi:10.1016/j.heliyon.2026.e44753 · Cited by 1
Supercritical branching processes and the role of fluctuations under exponential population growth
Manrubia, S. C., Arribas, M., & Lázaro, E. (2003) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(03)00294-7 · Cited by 1
Efficiency of polymerase chain reaction processes: A stochastic model
Hassibi, A., & Sharif, M. (2006) · IEEE International Workshop on Genomic Signal Processing and Statistics · doi:10.1109/gensips.2006.353143 · Cited by 1
Gill, P., Bleka, Ø., Hansson, O., Benschop, C. C. G., & Haned, H. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-820562-4.00012-2 · Cited by 1
On the relation between input and output distributions of scRNA-seq experiments
Schwabe, D., & Falcke, M. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab841 · Cited by 2
Welch, R. D., Anderson, I., & Gorski, J. (1999) · Analytical Biochemistry · doi:10.1006/abio.1998.3055 · Cited by 1
Maximum a posteriori (MAP) estimator for polymerase chain reaction (PCR) processes
Kakavand, H., O'Brien, D., Hassibi, A., & Lee, T. H. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2004.1403854 · Cited by 1
A Bayesian Approach to the Quantitative Polymerase Chain Reaction
Lalam, N., & Jacob, C. (2007) · Birkhäuser Boston eBooks · doi:10.1007/978-0-8176-4556-4_27
Technological Aspects of Molecular Diagnosis of Bacterial Infectious Diseases
Booth, C. S. (2012) · Lincoln (University of Nebraska)
Bayesian estimation for quantification by real-time Polymerase Chain Reaction
Lalam, N., & Jacob, C. (2005) · TU/e Research Portal
SURVEY AND SUMMARY Validation of kinetics similarity in qPCR
Bar, T., Kubista, M., Tichopád, A., & Benes, E. (2011)
Statistical Applications in Genetics and Molecular Biology
Lalam, N. (2007)
A NONLINEAR RESPONSE MODEL FOR SINGLE NUCLEOTIDE POLYMORPHISM DETECTION ASSAYS
Kouri, D. (2008) · OhioLink ETD Center (Ohio Library and Information Network)
Metadata
- Authors
- Stolovitzky, G., & Cecchi, G.
- Affiliations
- Rockefeller University (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 1996-11-12
- Volume
- 93
- Issue
- 23
- Pages
- 12947-12952
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC24026
- OpenAlex
- W2004803703
- Cited by
- 112
- References
- 23
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 8 · 2020: 8 · 2019: 1 · 2018: 2 · 2017: 2 · 2016: 7 · 2015: 5 · 2014: 5 · 2013: 4 · 2012: 5
- FWCI
- 0.50
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Nucleic Acid Chemistry
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- PCR, DNA replication, kinetic model, PCR cycle number, multimodality, scaling behavior, real-time PCR
- MeSH terms
- DNA Replication, Kinetics, Models, Theoretical, Probability, Time Factors, Reproducibility of Results, Polymerase Chain Reaction
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
