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Oliver Shaw

dblp:95/4439 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene regulation
gene regulatory network
0.112007
Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach · Bioinform. 2007
Bioinformatics and computational biology
qualitative modeling
0.112007
Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach · Bioinform. 2007
Bioinformatics and computational biology › network bioinformatics
boolean network
0.012007
Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach · Bioinform. 2007
Bioinformatics and computational biology
gene expression
0.012007
Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach · Bioinform. 2007

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

petri nets · 0.1logic minimization · 0.1
YearPublicationVenuePosition
2007 Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach
abstract
MOTIVATION: New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. RESULTS: We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. AVAILABILITY: The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.
L. Jason Steggles, Richard Banks, Oliver Shaw, Anil Wipat
Bioinform.3