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A model for protein secondary structure prediction meta - Classifiers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present here a mathematical model for the Protein Secondary Structure Prediction (PSSP) problems and research. It also represents un effort to build a uniform foundations for PSSP research. The model, and hence the paper, is designed to facilitate and speed up understanding of the long standing PSSP research and its problems also for people who want to get involved in it. We present an abstract definition of a protein and its structures and discuss the Protein Data Banks, and other Proteomic Data Bases as well as three generations of PSSP algorithms and servers (all of them web-accessible). We also discuss the development of most important results, problems and methods of data preparation for PSSP classifiers. Finally, we describe a model for a Meta-Classifier utilizing all, or a subset of PSSP servers and discuss its relationship with the first ever developed, Bayes Network Meta-Classifiers of [13] based on 4 to 6 servers.

Original languageEnglish
Title of host publication2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008
DOIs
StatePublished - 2008
Event2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008 - New York City, NY, United States
Duration: May 19 2008May 22 2008

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008
Country/TerritoryUnited States
CityNew York City, NY
Period05/19/0805/22/08

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