Prediction of DNA-Binding Proteins from Relational Features
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00178390" target="_blank" >RIV/68407700:21230/10:00178390 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Prediction of DNA-Binding Proteins from Relational Features
Original language description
DNA-binding proteins have a vital role in the biological processing of genetic information like DNA transcription, replication, maintenance and the regulation of gene expression. Modelling of protein-DNA interactions has recently received signific ant attention. We use logic-based machine learning to distinguish DNA-binding proteins from non-binding proteins. We combine previously suggested coarse-grained features (proportional distribution of specific residues, spatial asymmetry of specific residues and dipole moment) wi th automatically constructed structural (spatial) features. Prediction based only on structural features already improves on the state-of-the-art predictive accuracies achieved in previous work with coarse-grained features. Accuraciesare further improved when the combination of both feature categories is used.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Workshop 2010
ISBN
978-80-01-04513-8
ISSN
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e-ISSN
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Number of pages
16
Pages from-to
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Publisher name
České vysoké učení technické v Praze
Place of publication
Praha
Event location
Praha
Event date
Feb 22, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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