NDLI: Using a mixture of probabilistic decision trees for direct prediction of protein function

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Using a mixture of probabilistic decision trees for direct prediction of protein function

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Using a mixture of probabilistic decision trees for direct prediction of protein function

Content Provider	ACM Digital Library
Author	Syed, Umar Yona, Golan
Abstract	We study the direct relationship between basic protein properties and their function. Our goal is to develop a new tool for functional prediction that can be used to complement and support other techniques based on sequence or structure information. In order to define this new measure of similarity between proteins we collected a set of 453 features and properties that characterize proteins and are believed to be correlated and related to structural and functional aspects of proteins. Among these properties are the composition and fraction of different groups of amino acids, predicted secondary structure content, molecular weight, average hydrophobicity, isoelectric point and others, as well as a set of properties that are extracted from database records of known protein sequences, such as subcellular location, tissue specificity, and others.We introduce the mixture model of probabilistic decision trees to learn the set of potentially complex relationships between features and function. To study these correlations, trees are created and tested on the Pfam sequence-based classification of proteins and the EC classification of enzyme families. The model is very effective in learning highly diverged protein families or families that are not defined based on sequence. The resulting tree structure indicates the properties that are strongly correlated with structural and functional aspects of protein families, and can be used to suggest a concise definition of a protein family.
Starting Page	289
Ending Page	300
Page Count	12
File Format	PDF
ISBN	1581136358
DOI	10.1145/640075.640114
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-04-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Functional prediction Sequence-function relationships Decision trees
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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