NDLI: A machine learning framework for trait based genomics

Content Provider	IEEE Xplore Digital Library
Author	Wei Zhang Erliang Zeng Dan Liu Jones, S. Emrich, S.
Copyright Year	2012
Description	Author affiliation: Department of Biological Science, University of Notre Dame, South Bend, Indiana 46556, USA (Dan Liu; Jones, S.) \|\| Department of Computer Science and Engineering, University of Notre Dame, South Bend, Indiana 46556, USA (Wei Zhang; Erliang Zeng; Emrich, S.)
Abstract	Microbial communities perform many important ecological functions across a wide range of natural and man-made environments. Recently, the utility of trait based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. In this paper, we proposed a machine learning framework to quantitatively link the genotype with functional traits. Genes from bacteria genomes belonging to different functional trait groups were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. We focused on a binary functional trait in this paper, but plan to extend our approach to continuous functional traits in the future. Experimental results demonstrated that functional trait related genes can be detected using our method.
Starting Page	1
Ending Page	6
File Size	227863
Page Count	6
File Format	PDF
ISBN	9781467313209
e-ISBN	9781467313216
e-ISBN	9781467313193
DOI	10.1109/ICCABS.2012.6182648
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Functional Trait Communities Genomics Ecology Microbial communities Machine Learning Ortholog Support vector machines Feature Selection Microorganisms Accuracy Bioinformatics Sequencing
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	Mr. Siddhartha Mukherjee siddhartha@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	ndl-support@iitkgp.ac.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray 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

Improving reliability of gene selection from microarray functional genomics data

Prediction of low coverage prone regions for Illumina sequencing projects using a support vector machine

EBGW_OMP: A sequence-based method for accurate prediction of outer membrane proteins

Feature selection for SNP data based on Relief-SVM

Feature selection in proteomic pattern data with support vector machines

A Layered Splice Site Prediction Algorithm Based on Feature Selection and Parameter Optimization

Breeding Value Estimate Based on Support Vector Machine

Comparison of feature selection techniques for viral DNA replication origin prediction

Predicting Thermophilic Nucleotide Sequences Based on Chaos Game Representation Features and Support Vector Machine

A machine learning framework for trait based genomics

Similar Documents

Improving reliability of gene selection from microarray functional genomics data

Prediction of low coverage prone regions for Illumina sequencing projects using a support vector machine

EBGW_OMP: A sequence-based method for accurate prediction of outer membrane proteins

Feature selection for SNP data based on Relief-SVM

Feature selection in proteomic pattern data with support vector machines

A Layered Splice Site Prediction Algorithm Based on Feature Selection and Parameter Optimization

Breeding Value Estimate Based on Support Vector Machine

Comparison of feature selection techniques for viral DNA replication origin prediction

Predicting Thermophilic Nucleotide Sequences Based on Chaos Game Representation Features and Support Vector Machine

A machine learning framework for trait based genomics