NDLI: Classification and clustering in metagenomics with unified data management and computational framework

Content Provider	IEEE Xplore Digital Library
Author	Rasheed, Z. Rangwala, H. Gillevet, P.
Copyright Year	2012
Description	Author affiliation: Microbiome Analysis Center, Department of Environmental Science and Policy, George Mason University, Fairfax, VA 22030 USA (Gillevet, P.) \|\| Department of Computer Science, George Mason University, Fairfax, VA 22030 USA (Rasheed, Z.; Rangwala, H.)
Abstract	The new generation of genomie technologies have allowed researchers to determine the collective DNA of organisms co-existing as communities across different environments. There is a need for the computational approaches to analyze and annotate the large volumes of available sequence data from such microbial communities (metagenomes). In this work, we develop an efficient and accurate metagenome classification and clustering approaches that reduce the computational complexity associated with comparing sequences. Our empirical results show the strength of the developed approaches in comparison to state-of-the-art algorithms with regards to computational efficiency and accuracy. We are also developing a web based metabiome portal that contains different computational tools and is used for the scalable, accurate, and easy analysis of large volumes of data available for the human metabiome.
Starting Page	965
Ending Page	967
File Size	286851
Page Count	3
File Format	PDF
ISBN	9781467327466
e-ISBN	9781467327473
e-ISBN	9781467327442
DOI	10.1109/BIBMW.2012.6470285
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Communities Genomics hashing species diversity Classification algorithms classification system biology Systems biology Clustering algorithms metagenomics clustering Bioinformatics Portals
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

A Map-Reduce Framework for Clustering Metagenomes

A big data approach to metagenomics for all-food-sequencing

Evaluation of shotgun metagenomics sequence classification methods using in silico and in vitro simulated communities

LSH-Div: Species diversity estimation using locality sensitive hashing

Shared Nearest Neighbor Clustering in a Locality Sensitive Hashing Framework

Neural network-based taxonomic clustering for metagenomics

RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets

Alignment and clustering of phylogenetic markers - implications for microbial diversity studies

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data

Classification and clustering in metagenomics with unified data management and computational framework

Similar Documents

A Map-Reduce Framework for Clustering Metagenomes

A big data approach to metagenomics for all-food-sequencing

Evaluation of shotgun metagenomics sequence classification methods using in silico and in vitro simulated communities

LSH-Div: Species diversity estimation using locality sensitive hashing

Shared Nearest Neighbor Clustering in a Locality Sensitive Hashing Framework

Neural network-based taxonomic clustering for metagenomics

RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets

Alignment and clustering of phylogenetic markers - implications for microbial diversity studies

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data

Classification and clustering in metagenomics with unified data management and computational framework