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Jose M. G. Vilar

dblp:65/8323 · DBLP profile ↗
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2ranked-venue papers
2as 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 · 2 · 2 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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis
gene expression modeling
0.112010
CplexA: a Mathematica package to study macromolecular-assembly control of gene expression · Bioinform. 2010

Methods — techniques the papers use, named apart from their topics

statistical mechanics · 0.1functional programming · 0.1
YearPublicationVenuePosition
2010 CplexA: a Mathematica package to study macromolecular-assembly control of gene expression
abstract
SUMMARY: Macromolecular assembly coordinates essential cellular processes, such as gene regulation and signal transduction. A major challenge for conventional computational methods to study these processes is tackling the exponential increase of the number of configurational states with the number of components. CplexA is a Mathematica package that uses functional programming to efficiently compute probabilities and average properties over such exponentially large number of states from the energetics of the interactions. The package is particularly suited to study gene expression at complex promoters controlled by multiple, local and distal, DNA binding sites for transcription factors. AVAILABILITY: CplexA is freely available together with documentation at http://sourceforge.net/projects/cplexa/.
Jose M. G. Vilar, Leonor Saiz
Bioinform.1
2006 Signal Processing in the TGF-β Superfamily Ligand-Receptor Network
abstract
The TGF-beta pathway plays a central role in tissue homeostasis and morphogenesis. It transduces a variety of extracellular signals into intracellular transcriptional responses that control a plethora of cellular processes, including cell growth, apoptosis, and differentiation. We use computational modeling to show that coupling of signaling with receptor trafficking results in a highly versatile signal-processing unit, able to sense by itself absolute levels of ligand, temporal changes in ligand concentration, and ratios of multiple ligands. This coupling controls whether the response of the receptor module is transient or permanent and whether or not different signaling channels behave independently of each other. Our computational approach unifies seemingly disparate experimental observations and suggests specific changes in receptor trafficking patterns that can lead to phenotypes that favor tumor progression.
Jose M. G. Vilar, Ronald Jansen, Chris Sander
PLoS Comput. Biol.1