Kelley, David R.

Expanded encyclopaedias of DNA elements in the human and mouse genomes

The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature

Genomics and Chromatin DynamicsEpigenetics and DNA Methylation

Cited by 2,378

Effective gene expression prediction from sequence by integrating long-range interactions

Avsec, Ž., Agarwal, V., Visentin, D., Ledsam, J. R., Grabska-Barwinska, A., Taylor, K. R., Assael, Y., Jumper, J., Kohli, P., & Kelley, D. R. (2021) · Nature Methods

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 1,326

Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

Kelley, D. R., Snoek, J., & Rinn, J. L. (2016) · Genome Research

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 1,048

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

Kelley, D. R., Reshef, Y. A., Bileschi, M., Belanger, D., McLean, C. Y., & Snoek, J. (2018) · Genome Research

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 537

Transposable elements reveal a stem cell-specific class of long noncoding RNAs

Kelley, D., & Rinn, J. (2012) · Genome Biology

Chromosomal and Genetic VariationsCancer-related molecular mechanisms research

Cited by 531

Transcriptional and Epigenetic Dynamics during Specification of Human Embryonic Stem Cells

Gifford, C. A., Ziller, M. J., Gu, H., Trapnell, C., Donaghey, J., Tsankov, A., Shalek, A. K., Kelley, D. R., Shishkin, A. A., Issner, R., et al. (2013) · Cell

Pluripotent Stem Cells ResearchEpigenetics and DNA Methylation

Cited by 435

Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning

Bernstein, N. J., Fong, N. L., Lam, I., Roy, M. A., Hendrickson, D. G., & Kelley, D. R. (2020) · Cell Systems

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 280

Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation

Linder, J., Srivastava, D., Yuan, H., Agarwal, V., & Kelley, D. R. (2025) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 265

Cross-species regulatory sequence activity prediction

Kelley, D. R. (2020) · PLOS Computational Biology

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 228

Murine single-cell RNA-seq reveals cell-identity- and tissue-specific trajectories of aging

Kimmel, J. C., Penland, L., Rubinstein, N. D., Hendrickson, D. G., Kelley, D. R., & Rosenthal, A. Z. (2019) · Genome Research

Single-cell and spatial transcriptomicsGenetics, Aging, and Longevity in Model Organisms

Cited by 184

The genetic and biochemical determinants of mRNA degradation rates in mammals

Agarwal, V., & Kelley, D. R. (2022) · Genome Biology

RNA Research and SplicingRNA and protein synthesis mechanisms

Cited by 155

The genetic and biochemical determinants of mRNA degradation rates in mammals

Agarwal, V., & Kelley, D. (2022) · Genome biology

RNA Research and SplicingRNA and protein synthesis mechanisms

Cited by 155

scBasset: Sequence-based modeling of single cell ATAC-seq using convolutional neural networks

Yuan, H., & Kelley, D. R. (2021) · Nature Methods

Single-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Cited by 138

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Gschwind, A. R., Mualim, K. S., Karbalayghareh, A., Sheth, M. U., Dey, K. K., Jagoda, E., Nurtdinov, R. N., Xi, W., Tan, A. S., Jones, H., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory)

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 119

Novel insights from a multiomics dissection of the Hayflick limit

Chan, M., Yuan, H., Soifer, I., Maile, T. M., Wang, R. Y., Ireland, A., O'Brien, J. J., Goudeau, J., Chan, L. J., Vijay, T., et al. (2022) · eLife

Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model Organisms

Cited by 99

Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk

Reshef, Y. A., Finucane, H. K., Kelley, D. R., Gusev, A., Kotliar, D., Ulirsch, J. C., Hormozdiari, F., Nasser, J., O’Connor, L., van de Geijn, B., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 68

Differentiation reveals latent features of aging and an energy barrier in murine myogenesis

Kimmel, J. C., Yi, N., Roy, M., Hendrickson, D. G., & Kelley, D. R. (2021) · Cell Reports

Muscle Physiology and DisordersSingle-cell and spatial transcriptomics

Cited by 42