110 citations · 161 across the 5 of their papers we have counts for
5 papers
Global epistasis on fitness landscapes
Juan Diaz-Colunga, Abigail Skwara, Karna Gowda +4
Epistatic interactions between mutations add substantial complexity to adaptive landscapes, and are often thought of as detrimental to our ability to predict evolution. Yet, patter…
From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics
Susanna Manrubia, José A. Cuesta, Jacobo Aguirre +15
Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to t…
Asterias: a parallelized web-based suite for the analysis of expression and aCGH data
Andreu Alibes, Edward R. Morrissey, Andres Canada +4
Asterias (\url{http://www.asterias.info}) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parall…
Variable selection from random forests: application to gene expression data
Ramon Diaz-Uriarte, Sara Alvarez de Andres
Random forest is a classification algorithm well suited for microarray data: it shows excellent performance even when most predictive variables are noise, can be used when the numb…
Molecular Signatures from Gene Expression Data
Ramon Diaz-Uriarte
Motivation: ``Molecular signatures'' or ``gene-expression signatures'' are used to predict patients' characteristics using data from coexpressed genes. Signatures can enhance under…