Recent studies in protein sequence analysis have leveraged the power of unlabeled data. For example, the profile and mismatch neighborhood kernels have shown significant improveme...
Motivation: Existing methods for protein sequence analysis are generally firstorder and inherently assume that each position is independent. We develop a general framework for int...
Martin Madera, Ryan Calmus, Grant Thiltgen, Kevin ...
We present a novel framework to estimate protein-protein (PPI) and domain-domain (DDI) interactions based on a belief propagation estimation method that efficiently computes inter...
Faruck Morcos, Marcin Sikora, Mark S. Alber, Dale ...
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...