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Nature Methods|August 8, 2022
scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networksHan Yuan, David R KelleyGenome Biology|January 31, 2026
Parameter-efficient fine-tuning enables scalable transfer of regulatory sequence models to novel contextsHan Yuan, Johannes Linder, David R KelleyNature Genetics|January 8, 2025
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulationJohannes Linder, Divyanshi Srivastava, Han Yuan, et al.Plos Computational Biology|July 21, 2020
Cross-species regulatory sequence activity predictionDavid R KelleyJournal of Computational Biology : a Journal of Computational Molecular Cell Biology|March 10, 2011
Extracting between-pathway models from E-MAP interactions using expected graph compressionDavid R Kelley, Carl KingsfordGenome Biology|November 24, 2022
The genetic and biochemical determinants of mRNA degradation rates in mammalsVikram Agarwal, David R KelleyGenome Biology|March 12, 2010
Detection and correction of false segmental duplications caused by genome mis-assemblyDavid R Kelley, Steven L SalzbergGenome Research|February 25, 2021
Semisupervised adversarial neural networks for single-cell classificationJacob C Kimmel, David R KelleyBMC Bioinformatics|November 4, 2010
Clustering metagenomic sequences with interpolated Markov modelsDavid R Kelley, Steven L SalzbergNature Methods|October 13, 2020
Predicting 3D genome folding from DNA sequence with AkitaGeoff Fudenberg, David R Kelley, Katherine S PollardPageof 39