<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Navarro, A.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genómica Comparativa y Selección Natural. Aplicaciones en el Genoma Humano. Capítulo 1.6</style></title><secondary-title><style face="normal" font="default" size="100%">Evolución y Adaptacón. 150 años después del Origen de las Especies</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><publisher><style face="normal" font="default" size="100%">Obrapropia.</style></publisher><pub-location><style face="normal" font="default" size="100%">Valencia</style></pub-location><pages><style face="normal" font="default" size="100%">51-59</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;La b&amp;uacute;squeda de los eventos adaptativos a nivel molecular que ha diferenciado el genoma humano del de nuestro pariente vivo m&amp;aacute;s cercano, el chimpanc&amp;eacute;, ha sido una de las &amp;aacute;reas de mayor investigaci&amp;oacute;n en gen&amp;oacute;mica comparativa. Paralelamente, la predicci&amp;oacute;n funcional de variantes gen&amp;eacute;ticas en nuestra especie ha sido un &amp;aacute;rea de intenso desarrollo en bioinform&amp;aacute;tica. En este trabajo discutiremos resultados previos y otros m&amp;aacute;s recientes que dan cuenta de estos desarrollos. Veremos que en todos los casos la estimaci&amp;oacute;n de las presiones selectivas a nivel de los genes individuales o de los residuos de las prote&amp;iacute;nas son el denominador com&amp;uacute;n para discutir ambos aspectos. Finalmente mostraremos c&amp;oacute;mo el an&amp;aacute;lisis de estas presiones selectivas por grupos funcionales de genes resulta una alternativa viable y con suficiente poder estad&amp;iacute;stico para el an&amp;aacute;lisis de la adaptaci&amp;oacute;n y de las restricciones evolutivas a nivel gen&amp;oacute;mico.&amp;nbsp;&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">19</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Martin-Coello, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Ausio, J.</style></author><author><style face="normal" font="default" size="100%">Roldan, E. R.</style></author><author><style face="normal" font="default" size="100%">Gomendio, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sexual selection drives weak positive selection in protamine genes and high promoter divergence, enhancing sperm competitiveness</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Biol Sci</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">positive selection</style></keyword><keyword><style  face="normal" font="default" size="100%">sperm competition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19364735</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Phenotypic adaptations may be the result of changes in gene structure or gene regulation, but little is known about the evolution of gene expression. In addition, it is unclear whether the same selective forces may operate at both levels simultaneously. Reproductive proteins evolve rapidly, but the underlying selective forces promoting such rapid changes are still a matter of debate. In particular, the role of sexual selection in driving positive selection among reproductive proteins remains controversial, whereas its potential influence on changes in promoter regions has not been explored. Protamines are responsible for maintaining DNA in a compacted form in chromosomes in sperm and the available evidence suggests that they evolve rapidly. Because protamines condense DNA within the sperm nucleus, they influence sperm head shape. Here, we examine the influence of sperm competition upon protamine 1 and protamine 2 genes and their promoters, by comparing closely related species of Mus that differ in relative testes size, a reliable indicator of levels of sperm competition. We find evidence of positive selection in the protamine 2 gene in the species with the highest inferred levels of sperm competition. In addition, sperm competition levels across all species are strongly associated with high divergence in protamine 2 promoters that, in turn, are associated with sperm swimming speed. We suggest that changes in protamine 2 promoters are likely to enhance sperm swimming speed by making sperm heads more hydrodynamic. Such phenotypic changes are adaptive because sperm swimming speed may be a major determinant of fertilization success under sperm competition. Thus, when species have diverged recently, few changes in gene-coding sequences are found, while high divergence in promoters seems to be associated with the intensity of sexual selection.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Journal article Proceedings. Biological sciences / The Royal Society Proc Biol Sci. 2009 Apr 8.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">E. Capriotti</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Casadio, R.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms Codon/genetics Computational Biology/*methods *DNA Mutational Analysis Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Humans Iduronic Acid/analogs &amp; derivatives/metabolism *Point Mutation Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular *Genetic Predisposition to Disease Genetic Variation Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein *Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Proteins/chemistry/*genetics Tumor Suppressor Protein p53/genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17935148</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">198-204</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Predicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome-scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS-PROT. It achieves 82% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single-point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile-based information and the evolutionary estimation of the selective pressures at the codon level. The results of large-scale application of SeqProfCod over all annotated point mutations in SWISS-PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies.</style></abstract><notes><style face="normal" font="default" size="100%">Capriotti, Emidio Arbiza, Leonardo Casadio, Rita Dopazo, Joaquin Dopazo, Hernan Marti-Renom, Marc A Evaluation Studies Research Support, Non-U.S. Gov’t United States Human mutation Hum Mutat. 2008 Jan;29(1):198-204.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Minguez, P.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">From genes to functional classes in the study of biological systems</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms Chromosome Mapping/*methods Computer Simulation Gene Expression Profiling/methods *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">babelomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Multigene Family/*physiology Signal Transduction/*physiology *Software Systems Biology/*methods *User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17407596</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;BACKGROUND: With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed. RESULTS: Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics. CONCLUSION: Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Al-Shahrour, Fatima Arbiza, Leonardo Dopazo, Hernan Huerta-Cepas, Jaime Minguez, Pablo Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov’t England BMC bioinformatics BMC Bioinformatics. 2007 Apr 3;8:114.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tarraga, J.</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Gabaldón, T.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals Computational Biology/*methods Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genetic Techniques Humans *Internet Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Software User-Computer Interface</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical *Phylogeny Programming Languages Sequence Alignment Sequence Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17452346</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">W38-42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Phylemon is an online platform for phylogenetic and evolutionary analyses of molecular sequence data. It has been developed as a web server that integrates a suite of different tools selected among the most popular stand-alone programs in phylogenetic and evolutionary analysis. It has been conceived as a natural response to the increasing demand of data analysis of many experimental scientists wishing to add a molecular evolution and phylogenetics insight into their research. Tools included in Phylemon cover a wide yet selected range of programs: from the most basic for multiple sequence alignment to elaborate statistical methods of phylogenetic reconstruction including methods for evolutionary rates analyses and molecular adaptation. Phylemon has several features that differentiates it from other resources: (i) It offers an integrated environment that enables the direct concatenation of evolutionary analyses, the storage of results and handles required data format conversions, (ii) Once an outfile is produced, Phylemon suggests the next possible analyses, thus guiding the user and facilitating the integration of multi-step analyses, and (iii) users can define and save complete pipelines for specific phylogenetic analysis to be automatically used on many genes in subsequent sessions or multiple genes in a single session (phylogenomics). The Phylemon web server is available at http://phylemon.bioinfo.cipf.es.</style></abstract><notes><style face="normal" font="default" size="100%">Tarraga, Joaquin Medina, Ignacio Arbiza, Leonardo Huerta-Cepas, Jaime Gabaldon, Toni Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W38-42. Epub 2007 Apr 22.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Positive selection, relaxation, and acceleration in the evolution of the human and chimp genome</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Comput Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/genetics Animals *Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genome/*genetics Humans Pan troglodytes/*genetics *Selection (Genetics)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16683019</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">e38</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">For years evolutionary biologists have been interested in searching for the genetic bases underlying humanness. Recent efforts at a large or a complete genomic scale have been conducted to search for positively selected genes in human and in chimp. However, recently developed methods allowing for a more sensitive and controlled approach in the detection of positive selection can be employed. Here, using 13,198 genes, we have deduced the sets of genes involved in rate acceleration, positive selection, and relaxation of selective constraints in human, in chimp, and in their ancestral lineage since the divergence from murids. Significant deviations from the strict molecular clock were observed in 469 human and in 651 chimp genes. The more stringent branch-site test of positive selection detected 108 human and 577 chimp positively selected genes. An important proportion of the positively selected genes did not show a significant acceleration in rates, and similarly, many of the accelerated genes did not show significant signals of positive selection. Functional differentiation of genes under rate acceleration, positive selection, and relaxation was not statistically significant between human and chimp with the exception of terms related to G-protein coupled receptors and sensory perception. Both of these were over-represented under relaxation in human in relation to chimp. Comparing differences between derived and ancestral lineages, a more conspicuous change in trends seems to have favored positive selection in the human lineage. Since most of the positively selected genes are different under the same functional categories between these species, we suggest that the individual roles of the alternative positively selected genes may be an important factor underlying biological differences between these species.</style></abstract><notes><style face="normal" font="default" size="100%">Arbiza, Leonardo Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov’t United States PLoS computational biology PLoS Comput Biol. 2006 Apr;2(4):e38. Epub 2006 Apr 28.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">L. Conde</style></author><author><style face="normal" font="default" size="100%">Vaquerizas, J. M.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Reumers, J.</style></author><author><style face="normal" font="default" size="100%">Rousseau, F.</style></author><author><style face="normal" font="default" size="100%">Schymkowitz, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms Computer Graphics Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genotype Haplotypes Internet Linkage Disequilibrium *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Nucleic Acid Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide *Software User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://nar.oxfordjournals.org/cgi/content/full/34/suppl_2/W621</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">W621-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user’s data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Conde, Lucia Vaquerizas, Juan M Dopazo, Hernan Arbiza, Leonardo Reumers, Joke Rousseau, Frederic Schymkowitz, Joost Dopazo, Joaquin Research Support, Non-U.S. Gov’t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W621-5.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Duchi, S.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Burguet, J.</style></author><author><style face="normal" font="default" size="100%">Pantoja-Uceda, D.</style></author><author><style face="normal" font="default" size="100%">Pineda-Lucena, A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selective pressures at a codon-level predict deleterious mutations in human disease genes</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Amino Acid Substitution Codon/*genetics Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Humans Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Inborn/*genetics Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Molecular Sequence Data *Mutation Neoplasms/genetics Proteins/genetics *Selection (Genetics) Tumor Suppressor Protein p53/chemistry/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">p53 Genetic Diseases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16584746</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">358</style></volume><pages><style face="normal" font="default" size="100%">1390-404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega&lt;0.1) are significantly associated (p&lt;0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega&lt;0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.</style></abstract><notes><style face="normal" font="default" size="100%">Arbiza, Leonardo Duchi, Serena Montaner, David Burguet, Jordi Pantoja-Uceda, David Pineda-Lucena, Antonio Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov’t England Journal of molecular biology J Mol Biol. 2006 May 19;358(5):1390-404. Epub 2006 Mar 15.</style></notes></record></records></xml>