Demo Data from SIGIR 2026 / reviewers in the wild / expert
Richard J. Boys
dblp:220/1036
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology › model exchange format
systems biology model exchange |
0.1 | 1 | 2006 | Tools for the SBML Community · Bioinform. 2006 |
Methods — techniques the papers use, named apart from their topics
SBML · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | CaliBayes and BASIS: integrated tools for the calibration, simulation and storage of biological simulation modelsabstractDynamic simulation modelling of complex biological processes forms the backbone of systems biology. Discrete stochastic models are particularly appropriate for describing sub-cellular molecular interactions, especially when critical molecular species are thought to be present at low copy-numbers. For example, these stochastic effects play an important role in models of human ageing, where ageing results from the long-term accumulation of random damage at various biological scales. Unfortunately, realistic stochastic simulation of discrete biological processes is highly computationally intensive, requiring specialist hardware, and can benefit greatly from parallel and distributed approaches to computation and analysis. For these reasons, we have developed the BASIS system for the simulation and storage of stochastic SBML models together with associated simulation results. This system is exposed as a set of web services to allow users to incorporate its simulation tools into their workflows. Parameter inference for stochastic models is also difficult and computationally expensive. The CaliBayes system provides a set of web services (together with an R package for consuming these and formatting data) which addresses this problem for SBML models. It uses a sequential Bayesian MCMC method, which is powerful and flexible, providing very rich information. However this approach is exceptionally computationally intensive and requires the use of a carefully designed architecture. Again, these tools are exposed as web services to allow users to take advantage of this system. In this article, we describe these two systems and demonstrate their integrated use with an example workflow to estimate the parameters of a simple model of Saccharomyces cerevisiae growth on agar plates. Yuhui Chen, Conor Lawless, Colin S. Gillespie, Jake Wu, Richard J. Boys, Darren J. Wilkinson |
Briefings Bioinform. | 5 |
| 2006 | Tools for the SBML CommunityabstractMOTIVATION: SBML is quickly becoming the standard format to exchange biochemical models. The tools presented in this paper are loosely-coupled, and are intended to be incorporated into SBML aware applications. The rationale for this is to reduce the amount of repeated work carried out within the community and to create tools that offer a greater number of features to the end-user. AVAILABILITY: All tools described are available from http://www.basis.ncl.ac.uk/software and are licensed under GNU General Public License. Colin S. Gillespie, Darren J. Wilkinson, Carole J. Proctor, Daryl P. Shanley, Richard J. Boys, Thomas B. L. Kirkwood |
Bioinform. | 5 |
| 2005 | CaliBayes: Integration of GRID based simulation and data resources for Bayesian calibration of biological models
Richard J. Boys, Daniel Henderson, Thomas B. L. Kirkwood, Darren J. Wilkinson, W. Eryk Wolski |
BMC Bioinform. | 1 |