Award details

Prediction of protein fold and function using chemometrics

Reference	BIO14432
Principal Investigator / Supervisor	Professor Andrew Doig
Co-Investigators / Co-Supervisors	Professor Olaf Wolkenhauer
Institution	The University of Manchester
Department	Life Sciences
Funding type	Research
Value (£)	137,500
Status	Completed
Type	Research Grant
Start date	01/05/2001
End date	31/12/2003
Duration	32 months

Abstract

There is a great need for methods that can predict the properties of a protein given its gene sequence. We will use chemometrics to develop algorithms that can predict the fold, function and subcellular localisation of a protein. In a training set, sequences are quantified by the frequencies of amino acids, amino acid pairs and sequence motifs. SIMCA fuzzy clustering methods group the classes by fold or function. The results show which features of a protein sequence are responsible for determining its properties. The methods are applicable to any sequence, so we will analyse all yeast and human genes for which no function has been assigned. Our techniques will provide a powerful alternative when sequence comparison and alignment fails.

Summary

unavailable

Committee	Closed Committee - Biomolecular Sciences (BMS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Bioinformatics (Phase 2) (BIO) [1998-2000]
Funding Scheme	X – not Funded via a specific Funding Scheme

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