Demo Data from EDBT 2026 / reviewers in the wild / expert
Michal Galdzicki
dblp:83/9384
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-8392-8183ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems biology
model reuse |
0.2 | 1 | 2014 | A C library for retrieving specific reactions from the BioModels database · Bioinform. 2014 |
Bioinformatics and computational biology › systems biology › SBML
SBML model annotation |
0.2 | 1 | 2014 | A C library for retrieving specific reactions from the BioModels database · Bioinform. 2014 |
Bioinformatics and computational biology
systems biology |
0.2 | 1 | 2014 | A C library for retrieving specific reactions from the BioModels database · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
string search · 0.2semantic annotation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | A C library for retrieving specific reactions from the BioModels databaseabstractSUMMARY: We describe libSBMLReactionFinder, a C library for retrieving specific biochemical reactions from the curated systems biology markup language models contained in the BioModels database. The library leverages semantic annotations in the database to associate reactions with human-readable descriptions, making the reactions retrievable through simple string searches. Our goal is to provide a useful tool for quantitative modelers who seek to accelerate modeling efforts through the reuse of previously published representations of specific chemical reactions. AVAILABILITY AND IMPLEMENTATION: The library is open-source and dual licensed under the Mozilla Public License Version 2.0 and GNU General Public License Version 2.0. Project source code, downloads and documentation are available at http://code.google.com/p/lib-sbml-reaction-finder. Maxwell Lewis Neal, Michal Galdzicki, J. T. Gallimore, Herbert M. Sauro |
Bioinform. | 2 |
| 2013 | Identifying High-Risk Components in Synthetic Biology
Nikhil Gopal, Michal Galdzicki, Bryan Bartley, Evren Sirin, John H. Gennari |
AMIA | 2 |
| 2011 | Multiple ontologies in action: Composite annotations for biosimulation modelsabstractThere now exists a rich set of ontologies that provide detailed semantics for biological entities of interest. However, there is not (nor should there be) a single source ontology that provides all the necessary semantics for describing biological phenomena. In the domain of physiological biosimulation models, researchers use annotations to convey semantics, and many of these annotations require the use of multiple reference ontologies. Therefore, we have developed the idea of composite annotations that access multiple ontologies to capture the physics-based meaning of model variables. These composite annotations provide the semantic expressivity needed to disambiguate the often-complex features of biosimulation models, and can be used to assist with model merging and interoperability. In this paper, we demonstrate the utility of composite annotations for model merging by describing their use within SemGen, our semantics-based model composition software. More broadly, if orthogonal reference ontologies are to meet their full potential, users need tools and methods to connect and link these ontologies. Our composite annotations and the SemGen tool provide one mechanism for leveraging multiple reference ontologies. John H. Gennari, Maxwell Lewis Neal, Michal Galdzicki, Daniel L. Cook |
J. Biomed. Informatics | 3 |