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John W. May

dblp:135/5751 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular informatics › cheminformatics
atom mapping
0.212016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Bioinformatics and computational biology
enzymatic reaction analysis
0.212016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
metabolic pathway analysis
0.212016
Reaction Decoder Tool (RDT): extracting features from chemical reactions · Bioinform. 2016
Bioinformatics and computational biology › systems biology
metabolic modeling
0.212013
Metingear: a development environment for annotating genome-scale metabolic models · Bioinform. 2013

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

dynamic programming · 0.2database cross-referencing · 0.2chemical structure assignment · 0.2
YearPublicationVenuePosition
2016 Reaction Decoder Tool (RDT): extracting features from chemical reactions
abstract
UNLABELLED: Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. AVAILABILITY AND IMPLEMENTATION: This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder CONTACT: : [email protected] or [email protected].
Syed Asad Rahman, Gilliean Torrance, Lorenzo Baldacci, Sergio Martínez Cuesta, Franz Fenninger, Nimish Gopal, Saket Choudhary, John W. May, Gemma L. Holliday, Christoph Steinbeck, Janet M. Thornton
Bioinform.8
2013 Metingear: a development environment for annotating genome-scale metabolic models
abstract
UNLABELLED: Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. AVAILABILITY: Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.
John W. May, A. Gordon James, Christoph Steinbeck
Bioinform.1