Demo Data from EDBT 2026 / reviewers in the wild / expert
Peter Ruhdal Jensen
dblp:154/0380
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0003-2080-2070ORCID · reported
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 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 › constraint-based modeling
constraint-based metabolic modeling |
0.2 | 1 | 2014 | Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property · Bioinform. 2014 |
Bioinformatics and computational biology › systems biology › metabolic network analysis
elementary flux modes |
0.2 | 1 | 2014 | Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property · Bioinform. 2014 |
Bioinformatics and computational biology › systems biology
metabolic network analysis |
0.1 | 1 | 2014 | Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
mixed integer linear programming · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching propertyabstractMOTIVATION: Elementary flux mode (EFM) is a useful tool in constraint-based modeling of metabolic networks. The property that every flux distribution can be decomposed as a weighted sum of EFMs allows certain applications of EFMs to studying flux distributions. The existence of biologically infeasible EFMs and the non-uniqueness of the decomposition, however, undermine the applicability of such methods. Efforts have been made to find biologically feasible EFMs by incorporating information from transcriptional regulation and thermodynamics. Yet, no attempt has been made to distinguish biologically feasible EFMs by considering their graphical properties. A previous study on the transcriptional regulation of metabolic genes found that distinct branches at a branch point metabolite usually belong to distinct metabolic pathways. This suggests an intuitive property of biologically feasible EFMs, i.e. minimal branching. RESULTS: We developed the concept of minimal branching EFM and derived the minimal branching decomposition (MBD) to decompose flux distributions. Testing in the core Escherichia coli metabolic network indicated that MBD can distinguish branches at branch points and greatly reduced the solution space in which the decomposition is often unique. An experimental flux distribution from a previous study on mouse cardiomyocyte was decomposed using MBD. Comparison with decomposition by a minimum number of EFMs showed that MBD found EFMs more consistent with established biological knowledge, which facilitates interpretation. Comparison of the methods applied to a complex flux distribution in Lactococcus lactis similarly showed the advantages of MBD. The minimal branching EFM concept underlying MBD should be useful in other applications. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Siu Hung Joshua Chan, Christian Solem, Peter Ruhdal Jensen, Ping Ji 0001 |
Bioinform. | 3 |