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Christopher Reynolds

dblp:73/7065 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2009
0000-0002-8219-7462ORCID · 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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction analysis
0.112009
ProtorP: a protein-protein interaction analysis server · Bioinform. 2009
Bioinformatics and computational biology › protein structure analysis › quaternary structure
protein-protein interface characterization
0.112009
ProtorP: a protein-protein interaction analysis server · Bioinform. 2009
Bioinformatics and computational biology
structural bioinformatics
0.112009
ProtorP: a protein-protein interaction analysis server · Bioinform. 2009

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

physicochemical parameter computation · 0.1
YearPublicationVenuePosition
2009 ProtorP: a protein-protein interaction analysis server
abstract
SUMMARY: The PROTORP server analyses protein-protein associations in 3D structures. The server calculates a series of physical and chemical parameters of the protein interaction sites that contribute to the binding energy of the association. These parameters include, size and shape, intermolecular bonding, residue and atom composition and secondary structure contributions. The server is flexible, in that it allows users to analyse individual protein associations or large datasets of associations deposited in the PDB, or upload and analyse proprietary files. The properties calculated can be compared with parameter distributions for non-homologous datasets of different classes of protein associations provided on the server website. The server provides an efficient way of characterizing protein-protein associations of new or existing proteins, and a means of putting these values in the context of previously observed associations. AVAILABILITY: http://www.bioinformatics.sussex.ac.uk/protorp
Christopher Reynolds, David Damerell, Susan Jones
Bioinform.1