About our Computational Biology and Bioinformatics research group
The main focus of our Computational Biology and Bioinformatics research group is the integration of two fields of research: genomics and structural biology.
Professor Rohs can accept graduate students from the following Ph.D. Programs as primary thesis adviser: Computational Biology and Bioinformatics, Chemistry, Physics, and Computer Science.
Professor Rohs also advises graduate students from the Master's Program in Quantitative and Computational Biology and undergraduate students from the Bachelor's Program in Quantitative Biology.
Our primary goal is to reveal yet unknown molecular mechanisms underlying gene regulation using bioinformatics analyses of high-throughput sequencing and DNA methylation data of whole genomes, integrated with experimental molecular biology approaches.
J. Li, et al.:
Predicting DNA structure using a deep learning method
Nat. Commun. 15, 1243 (2024)
J.M. Sagendorf, et al.:
PNAbind: Structure-based prediction of protein-nucleic acid binding using graph neural networks
bioRxiv 2024.02.27.582387 (2024)
Y. Jiang, et al.:
Probing the role of the protonation state of a minor groove linker histidine in Exd-Hox-DNA binding.
J.A. Weller and R. Rohs:
DrugHIVE: A deep hierarchical variational autoencoder for the structure-based design of drug-like molecules.
R. Mitra, et al.:
DeepPBS: Geometric deep learning for interpretable prediction of protein-DNA binding specificity.
J. Li, et al.:
Deep DNAshape: Predicting DNA shape considering extended flanking regions using a deep learning method.
B.H. Cooper, et al.:
DNA binding specificity of all four Saccharomyces cerevisiae forkhead transcription factors.
T.P. Chiu, et al.:
Physicochemical models of protein-DNA binding with standard and modified base pairs.
10
Current Lab Members
10
Graduated Ph.D. Students
81
Published Peer-Reviewed Papers
2010
Est. at University of Southern California
4
Academic Department Affiliations
