A systematic approach to RNA-associated motif discovery

BioOptimizer: a Bayesian scoring function approach to motif discovery

MOTIVATION Transcription factors (TFs) bind directly to short segments on the genome, often within hundreds to thousands of base pairs upstream of gene transcription start sites, to regulate gene expression. The experimental determination of TFs binding sites is expensive and time-consuming. Many motif-finding programs have been developed, but no program is clearly superior in all situations. P...

BEAM web server: a tool for structural RNA motif discovery

Motivation RNA structural motif finding is a relevant problem that becomes computationally hard when working on high-throughput data (e.g. eCLIP, PAR-CLIP), often represented by thousands of RNA molecules. Currently, the BEAM server is the only web tool capable to handle tens of thousands of RNA in input with a motif discovery procedure that is only limited by the current secondary structure pr...

!e Role of RNA-Binding Motif 3 in Epithelial Ovarian Cancer: A Biomarker Discovery Approach

Expert Discovery: A web mining approach

Expert discovery is a quest in search of finding an answer to a question: “Who is the best expert of a specific subject in a particular domain within peculiar array of parameters?” Expert with domain knowledge in any field is crucial for consulting in industry, academia and scientific community. Aim of this study is to address the issues for expert-finding task in real-world community. Collabor...

A Combinatorial Approach for Motif Discovery in Unaligned DNA Sequences

Motif (conserved pattern) modelling and finding in unaligned DNA sequences is a fundamental problem in computational biology with important applications in understanding gene regulation. Biological approaches for this problem are tedious and time-consuming. Large amounts of genome sequence data and gene expression micro-array data let us solve this problem computationally. Most computer science...