Reviews & Analysis

Bayesian networks are increasingly important for integrating biological data and for inferring cellular networks and pathways. What are Bayesian networks and how are they used for inference?

Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them?

Programs such as MFOLD and ViennaRNA are widely used to predict RNA secondary structures. How do these algorithms work? Why can't they predict RNA pseudoknots? How accurate are they, and will they get better?

Statistical models called hidden Markov models are a recurring theme in computational biology. What are hidden Markov models, and why are they so useful for so many different problems?

There seem to be a lot of computational biology papers with 'Bayesian' in their titles these days. What's distinctive about 'Bayesian' methods?

Many sequence alignment programs use the BLOSUM62 score matrix to score pairs of aligned residues. Where did BLOSUM62 come from?

Sequence alignment methods often use something called a 'dynamic programming' algorithm. What is dynamic programming and how does it work?