Background: The explosive growth of biological data provides opportunities for new statistical and comparative analyses of large information sets, such as alignments comprising te...
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Background: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold ...
Background: Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed...