NEMo: An Evolutionary Model with Modularity for PPI Networks
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Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...
Ecosystems are the stage on which the play of evolution is acted. Inferring evolutionary processes from the spatial and temporal genetic patterns they produce in populations is challenging because ecosystems are highly complex, spatially structured, and te ...
Networks are commonly used to represent key processes in biology; examples include transcriptional regulatory networks, protein-protein interaction (PPI) networks, metabolic networks, etc. Databases store many such networks, as graphs, observed or inferred ...
Many important questions in molecular biology, evolution, and biomedicine can be addressed by comparative genomic approaches. One of the basic tasks when comparing genomes is the definition of measures of similarity (or dissimilarity) between two genomes, ...
Mary Ann Liebert2017
Networks are central in the modeling and analysis of many large-scale human and technical systems, and they have applications in diverse fields such as computer science, biology, social sciences, and economics. Recently, network mining has been an active a ...
EPFL2016
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Polyploid taxa represent excellent models to address the underpinnings of genome evolution and the building up of new species in heterogeneous environments. Here, we present an overview of recent works in the alpine Biscutella laevigata autopolyploid compl ...
2015
The deluge of sequenced whole-genome data has motivated the study of comparative genomics, which provides global views on genome evolution, and also offers practical solutions in deciphering the functional roles of components of genomes. A fundamental comp ...
EPFL2015
Recent advancements in DNA sequencing technologies, accompanied by parallel development of sophisticated computational methods, offer an unprecedented opportunity to explore and study the genetic material of many organisms. However, despite the tremendous ...
EPFL2013
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Modeling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events not only include addition and removal of vertices and edges but also duplication of vertices and their associated ...
Evolutionary algorithms are heuristic methods that operate on a population of individuals, which represent candidate solutions to optimization problems. Individuals with better quality, or fitness, are reproduced at a higher rate than less fit individuals ...
