Demo Data from EDBT 2026 / reviewers in the wild / expert
Robert P. Sheehan
dblp:172/0603
· DBLP profile ↗
2ranked-venue papers
0as 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
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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology
biochemical simulation |
0.2 | 1 | 2016 | BioNetGen 2.2: advances in rule-based modeling · Bioinform. 2016 |
Bioinformatics and computational biology
systems biology |
0.2 | 1 | 2016 | BioNetGen 2.2: advances in rule-based modeling · Bioinform. 2016 |
Methods — techniques the papers use, named apart from their topics
rule-based modeling · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | BioNetGen 2.2: advances in rule-based modelingabstract: BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation and analysis of larger and more complex models than previously possible. AVAILABILITY AND IMPLEMENTATION: Stable BioNetGen releases (Linux, Mac OS/X and Windows), with documentation, are available at http://bionetgen.org Source code is available at http://github.com/RuleWorld/bionetgen CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online. Leonard A. Harris, Justin S. Hogg, José Juan Tapia, John A. P. Sekar, Sanjana Gupta, Ilya Korsunsky, Arshi Arora, Dipak Barua, Robert P. Sheehan, James R. Faeder |
Bioinform. | 9 |
| 2015 | A Neutrophil Phenotype Model for Extracorporeal Treatment of SepsisabstractNeutrophils play a central role in eliminating bacterial pathogens, but may also contribute to end-organ damage in sepsis. Interleukin-8 (IL-8), a key modulator of neutrophil function, signals through neutrophil specific surface receptors CXCR-1 and CXCR-2. In this study a mechanistic computational model was used to evaluate and deploy an extracorporeal sepsis treatment which modulates CXCR-1/2 levels. First, a simplified mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors was developed, containing 16 ODEs and 43 parameters. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. The mathematical model was calibrated using experimental data from baboons administered a two-hour infusion of E coli and followed for a maximum of 28 days. Ensembles of parameters were generated using a Bayesian parallel tempering approach to produce model fits that could recreate experimental outcomes. Stepwise logistic regression identified seven model parameters as key determinants of mortality. Sensitivity analysis showed that parameters controlling the level of killer cell neutrophils affected the overall systemic damage of individuals. To evaluate rescue strategies and provide probabilistic predictions of their impact on mortality, time of onset, duration, and capture efficacy of an extracorporeal device that modulated neutrophil phenotype were explored. Our findings suggest that interventions aiming to modulate phenotypic composition are time sensitive. When introduced between 3-6 hours of infection for a 72 hour duration, the survivor population increased from 31% to 40-80%. Treatment efficacy quickly diminishes if not introduced within 15 hours of infection. Significant harm is possible with treatment durations ranging from 5-24 hours, which may reduce survival to 13%. In severe sepsis, an extracorporeal treatment which modulates CXCR-1/2 levels has therapeutic potential, but also potential for harm. Further development of the computational model will help guide optimal device development and determine which patient populations should be targeted by treatment. Alexander D. Malkin, Robert P. Sheehan, Shibin Mathew, William J. Federspiel, Heinz Redl, Gilles Clermont |
PLoS Comput. Biol. | 2 |