Knowles, David A.

Predicting splicing from primary sequence with deep learning

Jaganathan, K., Kyriazopoulou Panagiotopoulou, S., McRae, J. F., Darbandi, S. F., Knowles, D., Li, Y. I., Kosmicki, J. A., Arbelaez, J., Cui, W., Schwartz, G. B., et al. (2019) · Cell

RNA Research and SplicingGenomics and Rare Diseases

Cited by 2,853

Annotation-free quantification of RNA splicing using LeafCutter

Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics

RNA Research and SplicingGenomics and Phylogenetic Studies

Cited by 765

Mapping cis- and trans-regulatory effects across multiple tissues in twins

The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Grundberg, E., Small, K. S., Hedman, Å. K., Nica, A. C., Buil, A., Keildson, S., Bell, J. T., Yang, T.-P., Meduri, E., et al. (2012) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 729

RNA splicing is a primary link between genetic variation and disease

Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science

RNA Research and SplicingGenetic Associations and Epidemiology

Cited by 660

Therapeutic reduction of ataxin-2 extends lifespan and reduces pathology in TDP-43 mice

Becker, L. A., Huang, B., Bieri, G., Ma, R., Knowles, D. A., Jafar-Nejad, P., Messing, J., Kim, H. J., Soriano, A., Auburger, G., et al. (2017) · Nature

Amyotrophic Lateral Sclerosis ResearchGenetic Neurodegenerative Diseases

Cited by 571

Molecular Choreography of Acute Exercise

Contrepois, K., Wu, S., Moneghetti, K. J., Hornburg, D., Ahadi, S., Tsai, M.-S., Metwally, A. A., Wei, E., Lee-McMullen, B., Quijada, J. V., et al. (2020) · Cell

Exercise and Physiological ResponsesCardiovascular and exercise physiology

Cited by 502

Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements

Grundberg, E., Meduri, E., Sandling, J. K., Hedman, Å. K., Keildson, S., Buil, A., Busche, S., Yuan, W., Nisbet, J., Sekowska, M., et al. (2013) · The American Journal of Human Genetics

Epigenetics and DNA MethylationGenetic Associations and Epidemiology

Cited by 370

Batch effects and the effective design of single-cell gene expression studies

Tung, P.-Y., Blischak, J. D., Hsiao, C. J., Knowles, D. A., Burnett, J. E., Pritchard, J. K., & Gilad, Y. (2017) · Scientific Reports

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 356

Integrative transcriptomic analysis of the amyotrophic lateral sclerosis spinal cord implicates glial activation and suggests new risk genes

Humphrey, J., Venkatesh, S., Hasan, R., Herb, J. T., de Paiva Lopes, K., Küçükali, F., Byrska-Bishop, M., Evani, U. S., Narzisi, G., Fagegaltier, D., et al. (2023) · Nature Neuroscience

Amyotrophic Lateral Sclerosis ResearchSingle-cell and spatial transcriptomics

Cited by 138

Inferring relevant cell types for complex traits by using single-cell gene expression

Calderon, D., Bhaskar, A., Knowles, D. A., Golan, D., Raj, T., Fu, A. Q., & Pritchard, J. K. (2017) · The American Journal of Human Genetics

Genetic Associations and EpidemiologySingle-cell and spatial transcriptomics

Cited by 127

White matter abnormalities and cognition in aging and Alzheimer disease

Peter, C., Sathe, A., Shashikumar, N., Pechman, K. R., Workmeister, A. W., Jackson, T. B., Huo, Y., Mukherjee, S., Mez, J., Dumitrescu, L. C., et al. (2025) · JAMA Neurology

Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and Applications

Cited by 59

Welch-weighted Egger regression reduces false positives due to correlated pleiotropy in Mendelian randomization

Brown, B. C., & Knowles, D. A. (2021) · The American Journal of Human Genetics

Genetic Associations and EpidemiologyAdvanced Causal Inference Techniques

Cited by 15

SingleBrain: A Meta-Analysis of Single-Nucleus eQTLs Linking Genetic Risk to Brain Disorders

Jang, B., Kailash, B., Tokolyi, A., Cuddleston, W. H., Ravi, A., Jung, S.-H., Naito, T., Kim, B., Kim, M. S., Cho, M., et al. (2025) · medRxiv

Genetic Associations and EpidemiologySingle-cell and spatial transcriptomics

Cited by 11

Mosaic chromosomal alterations in blood are associated with an increased risk of Alzheimer’s disease

Naito, T., Hirata, K., Jang, B., Lakhani, C. M., Buonfiglioli, A., Lee, W.-P., Valladares, O., Wang, L.-S., Okada, Y., Won, H.-H., et al. (2025) · medRxiv

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 4

LRP2: A proteogenomics pipeline for long-read informed protein isoform analysis and discovery

Schertzer, M. D., Lewandowski, J. T., Watts, E. F., Rosenow, W., Mehlferber, M. M., Jeffery, E. D., Adamson, S. I., Bruand, J., Tseng, E., Neelamraju, Y., et al. (2026) · Bioinformatics

Advanced Proteomics Techniques and ApplicationsGenomics and Phylogenetic Studies

Cited by 0