Abstract
ABSTRACT: BACKGROUND: Some amino acid residues functionally interact with each other. This interaction will result in an evolutionary co-variation between these residues - coevolution. Our goal is to find these coevolving residues. RESULTS: We present six new methods for detecting coevolving residues. Among other things, we suggest measures that are variants of Mutual Information, and measures that use a multidimensional representation of each residue in order to capture the physico-chemical similarities between amino acids. We created a benchmarking system, in silico, able to evaluate these methods through a wide range of realistic conditions. Finally, we use the combination of different methods as a way of improving performance. CONCLUSION: Our best method (Row and Column Weighed Mutual Information) has an estimated accuracy increase of 63% over Mutual Information. Furthermore, we show that the combination of different methods is efficient, and that the methods are quite sensitive to the different conditions tested.
| Original language | English |
|---|---|
| Journal | Algorithms for Molecular Biology |
| Volume | 2 |
| Issue number | 12 |
| ISSN | 1748-7188 |
| DOIs | |
| Publication status | Published - 2007 |
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