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Robert J. Clifford

dblp:07/3410 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
0000-0001-8888-897XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
protein analysis
0.012004
Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms · Bioinform. 2004
Bioinformatics and computational biology
protein function prediction
0.012004
Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms · Bioinform. 2004
Bioinformatics and computational biology › statistical genetics
single nucleotide polymorphism analysis
0.012004
Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms · Bioinform. 2004
Bioinformatics and computational biology › genomics
variant analysis
0.012004
Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

pfam · 0.0hidden markov model · 0.0HMMER · 0.0
YearPublicationVenuePosition
2004 Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms
abstract
MOTIVATION: Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans. SNPs causing amino acid substitutions are of particular interest as candidates for loci affecting susceptibility to complex diseases, such as diabetes and hypertension. To efficiently screen SNPs for disease association, it is important to distinguish neutral variants from deleterious ones. RESULTS: We describe the use of Pfam protein motif models and the HMMER program to predict whether amino acid changes in conserved domains are likely to affect protein function. We find that the magnitude of the change in the HMMER E-value caused by an amino acid substitution is a good predictor of whether it is deleterious. We provide internet-accessible display tools for a genomewide collection of SNPs, including 7391 distinct non-synonymous coding region SNPs in 2683 genes. AVAILABILITY: http://lpgws.nci.nih.gov/cgi-bin/GeneViewer.cgi
Robert J. Clifford, Michael N. Edmonson, Cu Nguyen, Kenneth H. Buetow
Bioinform.1