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Liam J. McGuffin answers a few questions about this month's
new hot paper in the field of Computer Science.
From
>>September 2004
Field:
Computer Science
Article Title: Improvement of the GenTHREADER method for genomic fold recognition
Authors: McGuffin,
LJ;Jones, DT
Journal: BIOINFORMATICS
Volume: 19
Page: 874-881
Year: MAY 1 2003
* Univ Coll London, Dept Comp Sci, Bioinformat Grp, Gower St, London WC1E 6BT, England.
* Univ Coll London, Dept Comp Sci, Bioinformat Grp, London WC1E 6BT, England.
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 Why
do you think your paper is highly cited?
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The new method described in the paper allows for greater coverage and
reliability of structural annotations with little computational
overhead.
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The improved GenTHREADER method is widely used and freely
available to academics via our popular PSIPRED protein structure
prediction web server. Fast, fully automated structure prediction
methods such as GenTHREADER are becoming increasingly important
tools in the post-genomic era.
Does
it describe a new discovery or new methodology that's useful to
others?
This paper describes an improved methodology for accurately
recognizing protein folds on a genomic scale.
Could
you summarize the significance of your paper in layman's terms?
Determining the structure of a protein helps us to understand the
function of the encoding gene. Computational methods for genome-wide
prediction of protein structures, such as GenTHREADER, are many
times faster and cheaper than experimental techniques. The new
method described in the paper allows for greater coverage and
reliability of structural annotations with little computational
overhead. This is achieved by incorporating secondary structure
element alignments, secondary structure matching, structural
alignment profiles, and bi-directional scoring into the original
GenTHREADER protocol. The method has recently been used to maintain
the Genomic Threading Database, a comprehensive resource for
structural annotations of over 170 genomes.
How
did you become involved in this research?
The paper was the culmination of my Ph.D. thesis which
investigated fully automated methods for fold recognition.
Dr. Liam J. McGuffin
Research Fellow
Bioinformatics Unit
Department of Computer Science
University College London
London, UK
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ESI Special Topics,
September 2004
Citing URL - http://www.esi-topics.com/nhp/2004/september-04-Liam J. McGuffin.html
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