Using coevolution to improve protein subfamily classification

Automated Protein Subfamily Identification and Classification

Function prediction by homology is widely used to provide preliminary functional annotations for genes for which experimental evidence of function is unavailable or limited. This approach has been shown to be prone to systematic error, including percolation of annotation errors through sequence databases. Phylogenomic analysis avoids these errors in function prediction but has been difficult to...

Coevolution Analysis using Protein Sequences

Using Subclasses to Improve Classification Learning

We propose to use systematic simulation studies as opposed to the use of real-world benchmark datasets to better understand the behaviour, strengths and weaknesses of machine learning algorithms. Simulated data sets allow much better control and understanding of the nature of the learning problem than empirical benchmark data sets. To demonstrate the value of our proposed research methodology, ...

Using Dependency Analysis to Improve Question Classification

Question classification is a first necessary task of automatic question answering systems. Linguistic features play an important role in developing an accurate question classifier. This paper proposes to use typed dependencies which are extracted automatically from dependency parses of questions to improve accuracy of classification. Experiment results show that with only surface typed dependen...

CAPS: coevolution analysis using protein sequences

UNLABELLED Coevolution Analysis using Protein Sequences (CAPS) is a PERL based software that identifies co-evolution between amino acid sites. Blosum-corrected amino acid distances are used to identify amino acid co-variation. The phylogenetic sequence relationships are used to remove the phylogenetic and stochastic dependencies between sites. The 3D protein structure is used to identify the na...