NDLI: MP-PIPE: a massively parallel protein-protein interaction prediction engine

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MP-PIPE: a massively parallel protein-protein interaction prediction engine

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MP-PIPE: a massively parallel protein-protein interaction prediction engine

Content Provider	ACM Digital Library
Author	Green, James R. Golshani, Ashkan Schoenrock, Andrew Dehne, Frank Pitre, Sylvain
Abstract	Interactions among proteins are essential to many biological functions in living cells but experimentally detected interactions represent only a small fraction of the real interaction network. Computational protein interaction prediction methods have become important to augment the experimental methods; in particular sequence based prediction methods that do not require additional data such as homologous sequences or 3D structure information which are often not available. Our Protein Interaction Prediction Engine (PIPE) method falls into this category. Park has recently compared PIPE with the other competing methods and concluded that our method "significantly outperforms the others in terms of recall-precision across both the yeast and human data". Here, we present MP-PIPE, a new massively parallel PIPE implementation for large scale, high throughput protein interaction prediction. MP-PIPE enabled us to perform the first ever complete scan of the entire human protein interaction network; a massively parallel computational experiment which took three months of full time 24/7 computation on a dedicated SUN UltraSparc T2+ based cluster with 50 nodes, 800 processor cores and 6,400 hardware supported threads. The implications for the understanding of human cell function will be significant as biologists are starting to analyze the 130,470 new protein interactions and possible new pathways in Human cells predicted by MP-PIPE.
Starting Page	327
Ending Page	337
Page Count	11
File Format	PDF
ISBN	9781450301022
DOI	10.1145/1995896.1995946
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-05-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	High throughput Massively parallel application Protein interaction prediction Computational biology
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
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