| Predicting effective microRNA target sites in mammalian mRNAs V Agarwal, GW Bell, JW Nam, DP Bartel elife 4, e05005, 2015 | 7809 | 2015 |
| Expanded identification and characterization of mammalian circular RNAs JU Guo, V Agarwal, H Guo, DP Bartel Genome biology 15 (7), 409, 2014 | 1731 | 2014 |
| Effective gene expression prediction from sequence by integrating long-range interactions Z Avsec, V Agarwal*, D Visentin*, JR Ledsam, A Grabska-Barwinska, ... Nature Methods, 2021 | 1321 | 2021 |
| Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance R Denzler, V Agarwal, J Stefano, DP Bartel, M Stoffel Molecular cell 54 (5), 766-776, 2014 | 717 | 2014 |
| Global analyses of the effect of different cellular contexts on microRNA targeting JW Nam, OS Rissland, D Koppstein, C Abreu-Goodger, CH Jan, ... Molecular cell 53 (6), 1031-1043, 2014 | 409 | 2014 |
| Impact of microRNA levels, target-site complementarity, and cooperativity on competing endogenous RNA-regulated gene expression R Denzler, SE McGeary, V Agarwal, DP Bartel, M Stoffel Molecular cell 64 (3), 565-579, 2016 | 322 | 2016 |
| Predicting mRNA abundance directly from genomic sequence using deep convolutional neural networks V Agarwal, J Shendure Cell reports 31 (7), 2020 | 292 | 2020 |
| A systematic evaluation of the design and context dependencies of massively parallel reporter assays JC Klein*, V Agarwal*, F Inoue*, A Keith*, B Martin, M Kircher, N Ahituv, ... Nature Methods, 1-9, 2020 | 241 | 2020 |
| Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair W Chen, A McKenna, J Schreiber, M Haeussler, Y Yin, V Agarwal, ... Nucleic acids research 47 (15), 7989-8003, 2019 | 232 | 2019 |
| Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation J Linder, D Srivastava, H Yuan, V Agarwal, DR Kelley Nature Genetics 57 (4), 949-961, 2025 | 199 | 2025 |
| Genome-wide analysis reveals rapid and dynamic changes in miRNA and siRNA sequence and expression during ovule and fiber development in allotetraploid cotton (Gossypium … M Pang*, AW Woodward*, V Agarwal*, X Guan, M Ha, V Ramachandran, ... Genome Biol 10 (11), R122, 2009 | 185 | 2009 |
| lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements MG Gordon*, F Inoue*, B Martin*, M Schubach*, V Agarwal, S Whalen, ... Nature Protocols, 1-28, 2020 | 159 | 2020 |
| The genetic and biochemical determinants of mRNA degradation rates in mammals V Agarwal, DR Kelley Genome Biology, 2022 | 154 | 2022 |
| Interspecies regulation of microRNAs and their targets M Ha, M Pang, V Agarwal, ZJ Chen Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms 1779 (11 …, 2008 | 151 | 2008 |
| Predicting microRNA targeting efficacy in Drosophila V Agarwal, AO Subtelny, P Thiru, I Ulitsky, DP Bartel Genome biology 19 (1), 152, 2018 | 150 | 2018 |
| Functional testing of thousands of osteoarthritis-associated variants for regulatory activity JC Klein, A Keith, SJ Rice, C Shepherd, V Agarwal, J Loughlin, ... Nature communications 10 (1), 2434, 2019 | 112 | 2019 |
| Massively parallel characterization of transcriptional regulatory elements V Agarwal, F Inoue, M Schubach, D Penzar, BK Martin, PM Dash, ... Nature 639 (8054), 411-420, 2025 | 108* | 2025 |
| Transcription factor binding site orientation and order are major drivers of gene regulatory activity I Georgakopoulos-Soares, C Deng, V Agarwal, CSY Chan, J Zhao, ... Nature communications 14 (1), 2333, 2023 | 90 | 2023 |
| CodonBERT large language model for mRNA vaccines S Li, S Moayedpour, R Li, M Bailey, S Riahi, L Kogler-Anele, M Miladi, ... Genome research 34 (7), 1027-1035, 2024 | 84* | 2024 |
| Deciphering the impact of genomic variation on function Code of Conduct Committee (alphabetical by last name) Cody Sarah 33 Farrell ... Nature 633 (8028), 47-57, 2024 | 78* | 2024 |
David BartelProfessor of Biology, HHMI, MIT, Whitehead InstituteVerified email at wi.mit.edu
