seqBrowser_exportAnnotsREs_960Our software focuses on tools to build biophysical sequence-to-affinity models from high-throughput protein-DNA and protein-RNA binding data, and then using those models to predict in vivo binding in cellular conditions including chromatin accessibility, genetic polymorphisms, and protein concentrations. We build highly accurate biophysical sequence-to-affinity models by using robust regression methods while also accounting for multiple binding modes and platform-specific artifacts. In order to predict in vivo binding, we integrate our biophysical sequence-to-affinity models with (1) DNaseI hypersensitivity data to model chromatin accessibility, (2) dbSNP and other polymorphism data to model differential binding, and (3) transcriptome or proteome data to model RNA-binding and transcription factor protein concentrations. We also develop software for producing publication-quality Universal Sequence Logos for both fixed and variable length binding motifs. Lastly, the Riley Lab also develops pipelines for finding gene expression biomarkers for different disease phenotypes.

Further information about our online software packages can be found on each perspective software site:



Dr. Todd Riley
Assistant Professor of Biology
University of Massachusetts Boston
100 Morrissey Blvd. | ISC Building Room 4730
Boston, Massachusetts 02125
Phone: (617) 287-3236