Linder, Johannes

Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation

Linder, J., Srivastava, D., Yuan, H., Agarwal, V., & Kelley, D. R. (2025) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 265

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation

Bogard, N., Linder, J., Rosenberg, A. B., & Seelig, G. (2019) · Cell

RNA Research and SplicingRNA regulation and disease

Cited by 215

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences

Linder, J., Bogard, N., Rosenberg, A. B., & Seelig, G. (2020) · Cell Systems

RNA and protein synthesis mechanismsCRISPR and Genetic Engineering

Cited by 107

Optimizing 5’UTRs for mRNA-delivered gene editing using deep learning

Castillo-Hair, S., Fedak, S., Wang, B., Linder, J., Havens, K., Certo, M., & Seelig, G. (2024) · Nature Communications

RNA and protein synthesis mechanismsRNA Interference and Gene Delivery

Cited by 98

Deciphering the impact of genetic variation on human polyadenylation using APARENT2

Linder, J., Koplik, S. E., Kundaje, A., & Seelig, G. (2022) · Genome Biology

RNA Research and SplicingGenetic Associations and Epidemiology

Cited by 49