A Deep Neural Network for Predicting and Engineering Alternative PolyadenylationNicholas Bogard, Georg Seelig, Johannes Linder et al.|Cell|2019Cited by 243
A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein SequencesJohannes Linder, Georg Seelig, Alexander Rosenberg et al.|Cell Systems|2020Cited by 122
Optimizing 5’UTRs for mRNA-delivered gene editing using deep learningSebastian M. Castillo-Hair, Georg Seelig, Michael Certo et al.|Nature Communications|2024Cited by 73
Fast activation maximization for molecular sequence designJohannes Linder, Georg Seelig|BMC Bioinformatics|2021Cited by 62
Deciphering the impact of genetic variation on human polyadenylation using APARENT2Johannes Linder, Georg Seelig, Anshul Kundaje et al.|Genome biology|2022Cited by 59