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Protein family comparison using statistical models and predicted structural information |
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| Authors: | Richard?Chung,Golan?Yona author-information" > author-information__contact u-icon-before" > mailto:golan@cs.cornell.edu" title=" golan@cs.cornell.edu" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author |
| Affiliation: | (1) Department of Computer Science, Cornell University, Ithaca, NY 14850, USA |
| Abstract: | BackgroundThis paper presents a simple method to increase the sensitivity of protein family comparisons by incorporating secondary structure (SS) information. We build upon the effective information theory approach towards profile-profile comparison described in [Yona & Levitt 2002]. Our method augments profile columns using PSIPRED secondary structure predictions and assesses statistical similarity using information theoretical principles. |
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