Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Background: The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data ...
Eric H. Baehrecke, Niem Dang, Ketan Babaria, Ben S...
Background: Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology...
Saikat Chakrabarti, Nitin Bhardwaj, Prem A. Anand,...
Background: The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a sim...
Background: Several in silico methods exist that were developed to predict protein interactions from the copious amount of genomic and proteomic data. One of these methods is Doma...