Ruipeng Lu

TL;DR: Information theory (IT) is applied to predict and prioritize noncoding variants of uncertain significance in regulatory, coding, and intronic regions based on changes in binding sites in these genes.

TL;DR: A novel motif discovery pipeline based on recursive, thresholded entropy minimization distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs.

TL;DR: A strategy for complete gene sequence analysis followed by a unified framework for interpreting non-coding variants that may affect gene expression is presented and large numbers of variants detected by NGS are distilled to a limited set of variants prioritized as potential deleterious changes.

TL;DR: Multiple information-dense TFBS clusters in promoters appear to protect promoters from effects of deleterious binding site mutations in a single TFBS that would otherwise alter regulation of these genes.

TL;DR: This approach distills large numbers of variants detected by NGS to a limited set of variants prioritized as potential deleterious changes and presents a strategy for complete gene sequence analysis followed by a unified framework for interpreting non-coding variants that may affect gene expression.