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A combined approach for genome wide protein function annotation/prediction

Publication Type : Journal Article

Publisher : Proteome Science 11/2013; 11(Suppl 1):S1

Source : Proteome Science 11/2013; 11(Suppl 1):S1

Url : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909112/

Campus : Amritapuri

School : School of Biotechnology

Department : biotechnology

Year : 2013

Abstract : genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent stakeholders in almost all biological processes, and therefore the need to precisely know their functions for a better understanding of the underlying biological mechanism is inevitable. The challenge of annotating uncharacterized proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions

Cite this Research Publication : Alfredo Benso, Stefano Di Carlo, Hafeez Ur Rehman, Gianfranco Politano, Alessandro Savino, Prashanth Suravajhala: A combined approach for genome wide protein function annotation/prediction. Proteome Science 11/2013; 11(Suppl 1):S1

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