Kelly Cochran

Hello!


I'm a PhD Candidate studying computational biology at Stanford. My thesis work in the Kundaje Lab has been developing ProCapNet, a deep learning model that predicts transcription initiation from DNA sequence alone. Interpreting ProCapNet provides insights into how the human genome encodes gene regulation, ultimately improving our understanding of genetic causes of disease.

I love teaching as much as I love science -- mostly CS109, Stanford's Intro to Probability course, where we build all the way up from fundamentals to the theory behind machine learning. I've also mentored several junior scientists (high school and undergrad) throughout my PhD.

Before Stanford, I worked with Dr. Shaun Mahony at Penn State University. We studied how well sequence models transfer across species, including how a simple domain adaptation strategy can reduce model mispredictions in transposable elements.

I graduated from Duke University with a Bachelor's in Computer Science and Minors in Statistics and Computational Biology, where I started my research career in the lab of Dr. Jeremy Kay, investigating isoform diversity in neuron cell-surface receptors. I also proudly served as drum major of the Duke University Marching Band.

In my free time, I volunteer at Pets In Need Palo Alto, rock climb, bake, and make music with the Stanford Laptop Orchestra.

Presenting the ProCapNet poster at CSHL's Biology of Genomes 2023!
Guiding students through defining a Binomial random variable in CS109 lecture.

Publications


Chen, Y., Shah, S.R., Leung, A., Paramo, M.I., Cochran, K., Kundaje, A., Clark, A.G., Lis, J.T., Yu, H. 2024. Directionality of transcriptional regulatory elements. bioRxiv.

Mudge, J.M., Carbonell-Sala, S., Diekhans, M., Gonzalez-Martinez, J., Hunt, T., Jungreis, I., Loveland, J.E., Arnan, C., Barnes, I., Bennett, R., Berry, A., Bignell, A., Cerdán-Vélez, D., Cochran, K., Cortés, L.T., Davidson, C., Donaldson, S., Dursun, C., Fatima, R., Hardy, M., Hebbar, P., Hollis, Z., James, B.T., Jiang, Y., Johnson, R., Kaur, G., Kay, M., Mangan, R.J., Maquedano, M., Gómez, L.M., Mathlouthi, N., Merritt, R., Ni, P., Palumbo, E., Perteghella, T., Pozo, F., Raj, S., Sisu, C., Steed, E., Sumathipala, D., Suner, M., Uszczynska-Ratajczak, B., Wass, E., Yang, Y.T., Zhang, D., Finn, R.D., Gerstein, M., Guigó, R., Hubbard, T.J.P., Kellis, M., Kundaje, A., Paten, B., Tress, M.L., Birney, E., Martin, F.J., Frankish, A. 2024. GENCODE 2025: reference gene annotation for human and mouse. Nucleic Acids Research. gkae1078.

Kaur, G., Perteghella, T., Carbonell-Sala, S., Gonzalez-Martinez, J., Hunt, T., Madry, T., Jungreis, I., Arnan, C., Lagarde, J., Borsari, B., Sisu, C., Jiang, Y., Bennett, R., Berry, A., Cerdán-Vélez, D., Cochran, K., Vara, C., Davidson, C., Donaldson, S., Dursun, C., González-López, S., Das, S.G., Hardy, M., Hollis, Z., Kay, M., Montañés, J.C., Ni, P., Nurtdinov, R., Palumbo, E., Pulido-Quetglas, C., Suner, M., Yu, X., Zhang, D., Loveland, J.E., Albà, M.M., Diekhans, M., Tanzer, A., Mudge, J.M., Flicek, P., Martin, F.J., Gerstein, M., Kellis, M., Kundaje, A., Paten, B., Tress, M.L., Johnson, R., Uszczynska-Ratajczak, B., Frankish, A., Guigó, R. 2024. GENCODE: massively expanding the lncRNA catalog through capture long-read RNA sequencing. bioRxiv.

Cochran, K., Yin, M., Mantripragada, A., Schreiber, J., Marinov, G., Shah, S.R., Yu, H., Lis, J.T., & Kundaje, A. 2024. Dissecting the cis-regulatory syntax of transcription initiation with deep learning. bioRxiv.

Martyn, G.E., Montgomery, M.T., Jones, H., Guo, K., Doughty, B.R., Linder, J., Chen, Z., Cochran, K., Lawrence, K.A., Munson, G., Pampari, A., Fulco, C.P., Kelley, D.R., Lander, E.S., Kundaje, A., Engreitz, J.M. 2023. Rewriting regulatory DNA to dissect and reprogram gene expression. bioRxiv.

Cochran, K., Srivastava, D., Shrikumar, A., Balsubramani, A., Hardison, R.C., Kundaje, A., & Mahony, S. 2022. Domain-adaptive neural networks improve cross-species transcription factor binding prediction. Genome Research. 32(3): pp. 512-523.

Ray, T., Cochran, K., Kozlowski, C., Wang. J., Alexander, G., Cady, M.A., Spencer. W.J., Ruzycki, P.A., Clark, B.S., Laeremans, A., He, M-X., Wang, X., Park, E., Hao, Y., Iannaccone, A., Hu, G., Fedrigo, O., Skiba, N.P., Arshavsky, V.Y., & Kay, J.N. 2020. Comprehensive identification of mRNA isoforms reveals the diversity of neural cell-surface molecules with roles in retinal development and disease. Nature Communications. 11(1): pp. 1-20.

Ray, T., Cochran, K., & Kay, J. 2019. The enigma of CRB1 and CRB1 retinopathies. In: Bowes Rickman C., Grimm C., Anderson R., Ash J., LaVail M., Hollyfield J. (eds) Retinal Degenerative Diseases. Advances in Experimental Medicine and Biology, vol 1185. Springer, Cham.