Publication List

@article{Toll-Riera2012a,
title = {Structure and age jointly influence rates of protein evolution.},
author = {Toll-Riera, Macarena and Bostick, David and Albà, M Mar and Plotkin, Joshua B},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3364943&tool=pmcentrez&rendertype=abstract},
issn = {1553-7358},
year = {2012},
date = {2012-01-01},
journal = {PLoS computational biology},
volume = {8},
number = {5},
pages = {e1002542},
abstract = {What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group - including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution.},
keywords = {Animals, Binding Sites, Computational Biology, Eukaryota, Evolution, Humans, Mice, Molecular, Protein Conformation, Protein Stability, Proteins, Proteins: chemistry, Proteins: genetics, Proteins: metabolism, Solvents}
}

@article{Blanco2006,
title = {ABS: a database of Annotated regulatory Binding Sites from orthologous promoters.},
author = {Blanco, Enrique and Farré, Domènec and Albà, M Mar and Messeguer, Xavier and Guigó, Roderic},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1347478&tool=pmcentrez&rendertype=abstract},
issn = {1362-4962},
year = {2006},
date = {2006-01-01},
journal = {Nucleic acids research},
volume = {34},
number = {Database issue},
pages = {D63--7},
abstract = {Information about the genomic coordinates and the sequence of experimentally identified transcription factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS (http://genome.imim.es/datasets/abs2005/index.html) is a public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addition, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs.},
keywords = {Animals, Binding Sites, Chickens, Chickens: genetics, Databases, Genetic, Genomics, Humans, Internet, Mice, Nucleic Acid, Promoter Regions, Rats, Transcription Factors, Transcription Factors: metabolism, User-Computer Interface}
}

@article{Messeguer2002,
title = {PROMO: detection of known transcription regulatory elements using species-tailored searches.},
author = {Messeguer, Xavier and Escudero, Ruth and Farré, Domènec and Núñez, Oscar and Martínez, Javier and Albà, M Mar},
url = {http://www.ncbi.nlm.nih.gov/pubmed/11847087},
issn = {1367-4803},
year = {2002},
date = {2002-01-01},
journal = {Bioinformatics (Oxford, England)},
volume = {18},
number = {2},
pages = {333--4},
abstract = {We have developed a set of tools to construct positional weight matrices from known transcription factor binding sites in a species or taxon-specific manner, and to search for matches in DNA sequences.},
keywords = {Animals, Binding Sites, Binding Sites: genetics, Computational Biology, DNA, DNA: genetics, DNA: metabolism, Humans, Software, Species Specificity, Transcription Factors, Transcription Factors: metabolism}
}