Demo Data from SIGIR 2026 / reviewers in the wild / expert
David Sichau
dblp:165/0699
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 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 › computational developmental biology
morphogenesis modeling |
0.2 | 1 | 2015 | LBIBCell: a cell-based simulation environment for morphogenetic problems · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
lattice boltzmann method · 0.2immersed boundary method · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | LBIBCell: a cell-based simulation environment for morphogenetic problemsabstractMOTIVATION: The simulation of morphogenetic problems requires the simultaneous and coupled simulation of signalling and tissue dynamics. A cellular resolution of the tissue domain is important to adequately describe the impact of cell-based events, such as cell division, cell-cell interactions and spatially restricted signalling events. A tightly coupled cell-based mechano-regulatory simulation tool is therefore required. RESULTS: We developed an open-source software framework for morphogenetic problems. The environment offers core functionalities for the tissue and signalling models. In addition, the software offers great flexibility to add custom extensions and biologically motivated processes. Cells are represented as highly resolved, massless elastic polygons; the viscous properties of the tissue are modelled by a Newtonian fluid. The Immersed Boundary method is used to model the interaction between the viscous and elastic properties of the cells, thus extending on the IBCell model. The fluid and signalling processes are solved using the Lattice Boltzmann method. As application examples we simulate signalling-dependent tissue dynamics. AVAILABILITY AND IMPLEMENTATION: The documentation and source code are available on http://tanakas.bitbucket.org/lbibcell/index.html Simon Tanaka, David Sichau, Dagmar Iber |
Bioinform. | 2 |