Publications

Cofer EM, Raimundo J, Tadych A, Yamazaki Y, Wong AK, Theesfeld CL, Levine MS, Troyanskaya OG. Modeling transcriptional regulation of model species with deep learning. Genome Research, April 2021. doi:10.1101/gr.266171.120. [GitHub][Website]

Le Goallec A*, Tierney BT*, Luber JM, Cofer EM, Kostic AD, and Patel CJ. A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type. PLOS Computational Biology, May 2020. doi:10.1371/journal.pcbi.1007895. (*Equal contribution)

Chen KM*, Cofer EM*, Zhou J, and Troyanskaya OG. Selene: a PyTorch-based deep learning library for sequence data. Nature Methods, March 2019. doi:10.1038/s41592-019-0360-8. [GitHub] (*Equal contribution)

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow P, Zietz M, Hoffman MM, Xie W, Rosen GL, Lengerich BJ, Israeli J, Lanchantin J, Woloszynek S, Carpenter AE, Shrikumar A, Xu J, Cofer EM, Lavender CA, Turaga SC, Alexandari AM, Zhiyong L, Harris DJ, DeCaprio D, Qi Y, Kundaje A, Peng Y, Wiley LK, Segler MHS, Boca SM, Swamidass J, Huang A, Gitter A*, and Greene CS*. Opportunities and obstacles for deep learning in biology and medicine. Journal of the Royal Society Interface, April 2018. doi:10.1098/rsif.2017.0387. [GitHub] (Randomized ordering where not marked by *)

Luber JM*, Tierney BT*, Cofer EM, Patel CJ, and Kostic AD. Aether: leveraging linear programming for optimal cloud computing in genomics. Bioinformatics, December 2017. doi:10.1093/bioinformatics/btx787. [GitHub] (*Equal contribution)


Preprints

Lee BD, Gitter A, Greene CS, Raschka S, Maguire F, Titus AJ, Kessler MD, Lee AJ,Chevrette MG, Stewart PA, Britto-Borges T, Cofer EM, Yu KH, Carmona JJ, FertigEJ, Kalinin AA, Signal B, Lengerich BJ, Triche TJ, and Boca SM. Ten quick tips for deep learning in biology. arXiv, May 2021.

Zhang Z*, Cofer EM*, and Troyanskaya OG. AMBIENT: Accelerated convolutional neural network architecture search for regulatory genomics. bioRxiv, January 2021. doi:10.1101/2021.02.25.432960. (*Equal contribution)

Cofer EM, Raimundo J, Tadych A, Yamazaki Y, Wong AK, Theesfeld CL, Levine MS, and Troyanskaya OG. DeepArk: modeling cis-regulatory codes of model species with deep learning. bioRxiv, April 2020. doi:10.1101/2020.04.23.058040. [GitHub] [Web server]

Chen KM*, Cofer EM*, Zhou J, and Troyanskaya OG. Selene: a PyTorch-based deep learning library for biological sequence-level data. bioRxiv, October 2018. doi:10.1101/438291. [GitHub] (*Equal contribution)

Luber JM*, Tierney BT*, Cofer EM, Patel CJ, and Kostic AD. Aether: leveraging linear programming for optimal cloud computing in genomics. bioRxiv, July 2017. doi:10.1101/162883. [GitHub] (*Equal contribution)

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow P, Xie W, Rosen GL, Lengerich BJ, Israeli J, Lanchantin J, Woloszynek S, Carpenter AE, Shrikumar A, Xu J, Cofer EM, Harris DJ, DeCaprio D, Qi Y, Kundaje A, Peng Y, Wiley LK, Segler MHS, Gitter A†, and Greene CS†. Opportunities and obstacles for deep learning in biology and medicine. bioRxiv, May 2017. doi:10.1101/142760. [GitHub] (Randomized ordering where not marked by †)