Markovian Modeling of Gene-Product Synthesis

Stochastic mRNA Synthesis in Mammalian Cells

Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y., & Tyagi, S. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040309 · Cited by 1,737

Intrinsic and extrinsic contributions to stochasticity in gene expression

Swain, P. S., Elowitz, M. B., & Siggia, E. D. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.162041399 · Cited by 1,661

Real-Time Kinetics of Gene Activity in Individual Bacteria

Golding, I., Paulsson, J., Zawilski, S. M., & Cox, E. C. (2005) · Cell · doi:10.1016/j.cell.2005.09.031 · Cited by 1,468

Intrinsic noise in gene regulatory networks

Thattai, M., & van Oudenaarden, A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.151588598 · Cited by 1,428

Control of Stochasticity in Eukaryotic Gene Expression

Raser, J. M., & O'Shea, E. K. (2004) · Science · doi:10.1126/science.1098641 · Cited by 1,425

Analytical distributions for stochastic gene expression

Shahrezaei, V., & Swain, P. S. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0803850105 · Cited by 829

Mammalian genes are transcribed with widely different bursting kinetics

Suter, D. M., Molina, N., Gatfield, D., Schneider, K., Schibler, U., & Naef, F. (2011) · Science · doi:10.1126/science.1198817 · Cited by 927

Using Gene Expression Noise to Understand Gene Regulation

Munsky, B., Neuert, G., & van Oudenaarden, A. (2012) · Science · doi:10.1126/science.1216379 · Cited by 745

Noise in protein expression scales with natural protein abundance

Bar-Even, A., Paulsson, J., Maheshri, N., Carmi, M., O'Shea, E., Pilpel, Y., & Barkai, N. (2006) · Nature Genetics · doi:10.1038/ng1807 · Cited by 807

Single-RNA counting reveals alternative modes of gene expression in yeast

Zenklusen, D., Larson, D. R., & Singer, R. H. (2008) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1514 · Cited by 684

Statistics or biology: the zero-inflation controversy about scRNA-seq data

Jiang, R., Sun, T., Song, D., & Li, J. J. (2022) · Genome Biology · doi:10.1186/s13059-022-02601-5 · Cited by 614

Genomic encoding of transcriptional burst kinetics

Larsson, A. J. M., Johnsson, P., Hagemann-Jensen, M., Hartmanis, L., Faridani, O. R., Reinius, B., Segerstolpe, Å., Rivera, C. M., Ren, B., & Sandberg, R. (2019) · Nature · doi:10.1038/s41586-018-0836-1 · Cited by 534

Nonlinear control of transcription through enhancer–promoter interactions

Zuin, J., Roth, G., Zhan, Y., Cramard, J., Redolfi, J., Piskadlo, E., Mach, P., Kryzhanovska, M., Tihanyi, G., Kohler, H., et al. (2022) · Nature · doi:10.1038/s41586-022-04570-y · Cited by 415

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Coulon, A., Chow, C. C., Singer, R. H., & Larson, D. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3484 · Cited by 309

Challenges in measuring and understanding biological noise

Eling, N., Morgan, M. D., & Marioni, J. C. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0130-6 · Cited by 247

Transcription in Living Cells: Molecular Mechanisms of Bursting

Rodriguez, J., & Larson, D. R. (2020) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-011520-105250 · Cited by 224

What Is a Transcriptional Burst?

Tunnacliffe, E., & Chubb, J. R. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.01.003 · Cited by 223

RNA velocity unraveled

Gorin, G., Fang, M., Chari, T., & Pachter, L. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010492 · Cited by 186

Digital Quantification of Proteins and mRNA in Single Mammalian Cells

Albayrak, C., Jordi, C. A., Zechner, C., Lin, J., Bichsel, C. A., Khammash, M., & Tay, S. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.02.030 · Cited by 176

Discrete Distributional Differential Expression (D 3 E) - A Tool for Gene Expression Analysis of Single-cell RNA-seq Data

Delmans, M., & Hemberg, M. (2015) · doi:10.1101/020735 · Cited by 111

Discrete distributional differential expression (D3E) - a tool for gene expression analysis of single-cell RNA-seq data

Delmans, M., & Hemberg, M. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-0944-6 · Cited by 111

Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods

Dal Molin, A., Baruzzo, G., & Di Camillo, B. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00062 · Cited by 107

Nonlinear control of transcription through enhancer-promoter interactions

Zuin, J., Roth, G., Zhan, Y., Cramard, J., Redolfi, J., Piskadlo, E., Mach, P., Kryzhanovska, M., Tihanyi, G., Kohler, H., et al. (2021) · doi:10.1101/2021.04.22.440891 · Cited by 67

Effects of DNA replication on mRNA noise

Peterson, J. R., Cole, J. A., Fei, J., Ha, T., & Luthey-Schulten, Z. A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1516246112 · Cited by 46

Pathway dynamics can delineate the sources of transcriptional noise in gene expression

Ham, L., Jackson, M., & Stumpf, M. P. (2021) · eLife · doi:10.7554/elife.69324 · Cited by 37

Regulation of spatiotemporal limits of developmental gene expression via enhancer grammar

Keller, S. H., Jena, S. G., Yamazaki, Y., & Lim, B. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1917040117 · Cited by 36

Mechanisms of transcription control by distal enhancers from high-resolution single-gene imaging

Cheng, L., De, C., Li, J., & Pertsinidis, A. (2023) · doi:10.1101/2023.03.19.533190 · Cited by 32

Distinguishing between models of mammalian gene expression: telegraph-like models versus mechanistic models

Braichenko, S., Holehouse, J., & Grima, R. (2021) · Journal of The Royal Society Interface · doi:10.1098/rsif.2021.0510 · Cited by 29

What can we learn when fitting a simple telegraph model to a complex gene expression model?

Jiao, F., Li, J., Liu, T., Zhu, Y., Che, W., Bleris, L., & Jia, C. (2024) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1012118 · Cited by 26

cgCorrect: a method to correct for confounding cell–cell variation due to cell growth in single-cell transcriptomics

Blasi, T., Buettner, F., Strasser, M. K., Marr, C., & Theis, F. J. (2017) · Physical Biology · doi:10.1088/1478-3975/aa609a · Cited by 18

Reduction of a stochastic model of gene expression: Lagrangian dynamics gives access to basins of attraction as cell types and metastabilty

Ventre, E., Espinasse, T., Bréhier, C.-E., Calvez, V., Lepoutre, T., & Gandrillon, O. (2021) · Journal of Mathematical Biology · doi:10.1007/s00285-021-01684-1 · Cited by 17

Short Residence Times of DNA-Bound Transcription Factors Can Reduce Gene Expression Noise and Increase the Transmission of Information in a Gene Regulation System

Azpeitia, E., & Wagner, A. (2020) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2020.00067 · Cited by 17

Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics

(2023) · doi:10.1063/5.0173742 · Cited by 14

Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression

(2025) · doi:10.1038/s41467-025-58127-4 · Cited by 13

Analysis of Single-Cell Gene Pair Coexpression Landscapes by Stochastic Kinetic Modeling Reveals Gene-Pair Interactions in Development

(2020) · doi:10.3389/fgene.2019.01387 · Cited by 8

Scalable inference and identifiability of kinetic parameters for transcriptional bursting from single cell data

(2025) · doi:10.1093/bioinformatics/btaf581 · Cited by 6

Cell-cycle dependence of transcription dominates noise in gene expression

Zopf, C. J., Quinn, K., Zeidman, J., & Maheshri, N. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003161 · Cited by 4

Modeling relaxation experiments with a mechanistic model of gene expression

Estavoyer, M., Dufeu, M., Ranson, G., Lefort, S., Voeltzel, T., Maguer-Satta, V., Gandrillon, O., & Lepoutre, T. (2024) · BMC Bioinformatics · doi:10.1186/s12859-024-05816-4

Nearly maximal information gain due to time integration in central dogma reactions

Sarkar, S., & Rammohan, J. (2023) · iScience · doi:10.1016/j.isci.2023.106767