A Deep Neural Network for Predicting and Engineering Alternative PolyadenylationNicholas Bogard, Georg Seelig, Johannes Linder et al.|Cell|2019Cited by 243
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulationJohannes Linder, David R. Kelley, Divyanshi Srivastava et al.|Nature Genetics|2025Cited by 163
A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein SequencesJohannes Linder, Georg Seelig, Nicholas Bogard et al.|Cell Systems|2020Cited by 122
Optimizing 5’UTRs for mRNA-delivered gene editing using deep learningSebastian M. Castillo-Hair, Georg Seelig, Stephen Fedak et al.|Nature Communications|2024Cited by 73
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulationJohannes Linder, David R. Kelley, Divyanshi Srivastava et al.|bioRxiv (Cold Spring Harbor Laboratory)|2023Cited by 64