Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
portfolio
CLIPNET Permalink
A deep learning approach to predicting transcription initiation from sequence at single nucleotide resolution.
LDetect-lite Permalink
Fast calculation of approximately independent linkage disequilibrium blocks.
PersonalBPNet Permalink
A small modification to bpnetlite’s BPNet to accomodate large validation datasets.
procap-atlas Permalink
Preprocessing and deep learning-based analysis of the ENCODE PRO-cap atlas.
promoterai-torch Permalink
A PyTorch port of PromoterAI, a deep learning model predicting the regulatory impact of promoter variants.
publications
Bcl-2 overexpression improves survival and efficacy of neural stem cell-mediated enzyme prodrug therapy
Published in Stem Cells International, 2018
Recommended citation: R. Mooney, A. A. Majid, D. Mota, S. Aramburo, A. Y. He, J. Covello-Batalla, D. Machado, J. Gonzaga, L. Flores, and K. S. Aboody. Bcl-2 overexpression improves survival and efficacy of neural stem cell-mediated enzyme prodrug therapy. Stem Cells Int. doi:10.1155/2018/7047496.
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Topological descriptions of protein folding
Published in Proceedings of the National Academy of Sciences of the United States of America, 2019
Recommended citation: E. Flapan, A. Y. He, and H. Wong. Topological descriptions of protein folding. Proc. Natl. Acad. Sci. U.S.A. doi:10.1073/pnas.1808312116.
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Using functional genomic data in monocytes/macrophages and genotyping to nominate disease-driving single nucleotide polymorphisms in juvenile idiopathic arthritis.
Published in BioRxiv, 2024
Recommended citation: E. K. Haley, G. Barshad, A. Y. He, E. J. Rice, M. Sudman, S. D. Thompson, E. A. Crinzi, K. Jiang, C. G. Danko, and J. N. Jarvis. Using functional genomic data in monocytes/macrophages and genotyping to nominate disease-driving single nucleotide polymorphisms in juvenile idiopathic arthritis. BioRxiv. doi:10.1101/2024.08.19.608312
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Training deep learning models on personalized genomic sequences improves variant effect prediction
Published in BioRxiv, 2024
Recommended citation: A. Y. He, N. P. Palamuttam, and C. G. Danko. Training deep learning models on personalized genomic sequences improves variant effect prediction. BioRxiv. doi.org/10.1101/2024.10.15.618510
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Peripheral blood cells as prognostic markers in patients with advanced non-small cell lung cancer treated with cemiplimab as monotherapy or in combination with chemotherapy
Published in Cancer Treatment and Research Communications, 2025
Recommended citation: R. J. Acosta, D. A. G. McIntyre, J. C. Murray, V. Anagnostou, J. R. Brahmer, A. Meisel, A. Sezer, M. Gogishvili, T. Melkadze, A. Baramidze, T. Makharadze, A. Y. He, V. Jankovic, G. P. Geba, A. Pillai, F. Seebach, P. Rietschel, G. Gullo, J.-F. Pouliot, and Y. Kim. Peripheral blood cells as prognostic markers in patients with advanced non-small cell lung cancer treated with cemiplimab as monotherapy or in combination with chemotherapy. Cancer Treat. Res. Commun. 44:100959. doi:10.1016/j.ctarc.2025.100959.
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Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation
Published in Nature Genetics, 2026
Recommended citation: A. Y. He and C. G. Danko. Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation. Nat. Genet. (in press)
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Functional and computational interrogation of juvenile idiopathic arthritis risk loci in CD4+ T cells
Published in HGG Advances, 2026
Recommended citation: K. Jiang, E. K. Haley, G. Barshad, A. Y. He, A. Rogic, E. Rice, M. Sudman, S. D. Thompson, D. A. Murphy, Y. Fu, L. Ponder, M. D. Munoz, P. Kolachala, S. Prahalad, P. M. Gaffney, C. G. Danko, and J. N. Jarvis. Functional and computational interrogation of juvenile idiopathic arthritis risk loci in CD4+ T cells. HGG Adv. 7(3):100619. doi:10.1016/j.xhgg.2026.100619
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pydreg: a fast Python package for identifying active cis-regulatory elements from nascent transcription
Published in BioRxiv, 2026
Recommended citation: A. Y. He and C. G. Danko. pydreg: a fast Python package for identifying active cis-regulatory elements from nascent transcription. BioRxiv. doi:10.64898/2026.09.06.745329
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talks
Dissection of core promoter architecture through single nucleotide-resolution modeling of transcription initiation
Published:
I gave a talk on CLIPNET at Mechanisms of Eukaryotic Transcription 2023. Slides can be found here.
Training deep learning models on personalized genomic sequences improves variant effect prediction
Published:
I gave a spotlight talk and poster on our work improving variant effect prediction by training sequence to function models on personal genomes at Machine Learning in Computational Biology 2024. Here is the Youtube recording of my presentation. The preprint for this paper is on bioRxiv.