@article {468, title = {PTMcode v2: a resource for functional associations of post-translational modifications within and between proteins.}, journal = {Nucleic Acids Res}, volume = {43}, year = {2015}, month = {2015 Jan}, pages = {D494-502}, abstract = {

The post-translational regulation of proteins is mainly driven by two molecular events, their modification by several types of moieties and their interaction with other proteins. These two processes are interdependent and together are responsible for the function of the protein in a particular cell state. Several databases focus on the prediction and compilation of protein-protein interactions (PPIs) and no less on the collection and analysis of protein post-translational modifications (PTMs), however, there are no resources that concentrate on describing the regulatory role of PTMs in PPIs. We developed several methods based on residue co-evolution and proximity to predict the functional associations of pairs of PTMs that we apply to modifications in the same protein and between two interacting proteins. In order to make data available for understudied organisms, PTMcode v2 (http://ptmcode.embl.de) includes a new strategy to propagate PTMs from validated modified sites through orthologous proteins. The second release of PTMcode covers 19 eukaryotic species from which we collected more than 300,000 experimentally verified PTMs (>1,300,000 propagated) of 69 types extracting the post-translational regulation of >100,000 proteins and >100,000 interactions. In total, we report 8 million associations of PTMs regulating single proteins and over 9.4 million interplays tuning PPIs.

}, keywords = {Databases, Protein, Internet, Protein Interaction Mapping, Protein Processing, Post-Translational}, issn = {1362-4962}, doi = {10.1093/nar/gku1081}, author = {Minguez, Pablo and Letunic, Ivica and Parca, Luca and Garc{\'\i}a-Alonso, Luz and Dopazo, Joaquin and Huerta-Cepas, Jaime and Bork, Peer} } @article {533, title = {Evidence for short-time divergence and long-time conservation of tissue-specific expression after gene duplication.}, journal = {Brief Bioinform}, volume = {12}, year = {2011}, month = {2011 Sep}, pages = {442-8}, abstract = {

Gene duplication is one of the main mechanisms by which genomes can acquire novel functions. It has been proposed that the retention of gene duplicates can be associated to processes of tissue expression divergence. These models predict that acquisition of divergent expression patterns should be acquired shortly after the duplication, and that larger divergence in tissue expression would be expected for paralogs, as compared to orthologs of a similar age. Many studies have shown that gene duplicates tend to have divergent expression patterns and that gene family expansions are associated with high levels of tissue specificity. However, the timeframe in which these processes occur have rarely been investigated in detail, particularly in vertebrates, and most analyses do not include direct comparisons of orthologs as a baseline for the expected levels of tissue specificity in absence of duplications. To assess the specific contribution of duplications to expression divergence, we combine here phylogenetic analyses and expression data from human and mouse. In particular, we study differences in spatial expression among human-mouse paralogs, specifically duplicated after the radiation of mammals, and compare them to pairs of orthologs in the same species. Our results show that gene duplication leads to increased levels of tissue specificity and that this tends to occur promptly after the duplication event.

}, keywords = {Animals, Conserved Sequence, Evolution, Molecular, Gene Duplication, gene expression, Genome, Humans, Mice, Organ Specificity}, issn = {1477-4054}, doi = {10.1093/bib/bbr022}, author = {Huerta-Cepas, Jaime and Dopazo, Joaquin and Huynen, Martijn A and Gabald{\'o}n, Toni} } @article {539, title = {Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.}, journal = {Nucleic Acids Res}, volume = {39}, year = {2011}, month = {2011 Jul}, pages = {W470-4}, abstract = {

Phylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing.

}, keywords = {Evolution, Molecular, Genomics, Internet, Phylogeny, Sequence Alignment, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkr408}, author = {S{\'a}nchez, Rub{\'e}n and Serra, Fran{\c c}ois and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and De Maria, Alejandro and Capella-Gut{\'\i}errez, Salvador and Huerta-Cepas, Jaime and Gabald{\'o}n, Toni and Dopazo, Joaquin and Dopazo, Hern{\'a}n} } @article {548, title = {ETE: a python Environment for Tree Exploration.}, journal = {BMC Bioinformatics}, volume = {11}, year = {2010}, month = {2010 Jan 13}, pages = {24}, abstract = {

BACKGROUND: Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale.

RESULTS: Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE{\textquoteright}s programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations.

CONCLUSIONS: ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

}, keywords = {Computational Biology, Databases, Genetic, Phylogeny, Software}, issn = {1471-2105}, doi = {10.1186/1471-2105-11-24}, author = {Huerta-Cepas, Jaime and Dopazo, Joaquin and Gabald{\'o}n, Toni} } @article {20164864, title = {Fine-scale evolution: genomic, phenotypic and ecological differentiation in two coexisting Salinibacter ruber strains.}, journal = {The ISME journal}, year = {2010}, month = {2010 Feb 18}, abstract = {

Genomic and metagenomic data indicate a high degree of genomic variation within microbial populations, although the ecological and evolutive meaning of this microdiversity remains unknown. Microevolution analyses, including genomic and experimental approaches, are so far very scarce for non-pathogenic bacteria. In this study, we compare the genomes, metabolomes and selected ecological traits of the strains M8 and M31 of the hyperhalophilic bacterium Salinibacter ruber that contain ribosomal RNA (rRNA) gene and intergenic regions that are identical in sequence and were simultaneously isolated from a Mediterranean solar saltern. Comparative analyses indicate that S. ruber genomes present a mosaic structure with conserved and hypervariable regions (HVRs). The HVRs or genomic islands, are enriched in transposases, genes related to surface properties, strain-specific genes and highly divergent orthologous. However, the many indels outside the HVRs indicate that genome plasticity extends beyond them. Overall, 10\% of the genes encoded in the M8 genome are absent from M31 and could stem from recent acquisitions. S. ruber genomes also harbor 34 genes located outside HVRs that are transcribed during standard growth and probably derive from lateral gene transfers with Archaea preceding the M8/M31 divergence. Metabolomic analyses, phage susceptibility and competition experiments indicate that these genomic differences cannot be considered neutral from an ecological perspective. The results point to the avoidance of competition by micro-niche adaptation and response to viral predation as putative major forces that drive microevolution within these Salinibacter strains. In addition, this work highlights the extent of bacterial functional diversity and environmental adaptation, beyond the resolution of the 16S rRNA and internal transcribed spacers regions.The ISME Journal advance online publication, 18 February 2010; doi:10.1038/ismej.2010.6.

}, author = {Pe{\~n}a, Arantxa and Teeling, Hanno and Huerta-Cepas, Jaime and Santos, Fernando and Yarza, Pablo and Brito-Echeverr{\'\i}a, Jocelyn and Lucio, Marianna and Schmitt-Kopplin, Philippe and Meseguer, Inmaculada and Schenowitz, Chantal and Dossat, Carole and Barbe, Valerie and Joaqu{\'\i}n Dopazo and Rossell{\'o}-Mora, Ramon and Sch{\"u}ler, Margarete and Gl{\"o}ckner, Frank Oliver and Amann, Rudolf and Gabald{\'o}n, Toni and Ant{\'o}n, Josefa} } @article {593, title = {GEPAS, a web-based tool for microarray data analysis and interpretation.}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, month = {2008 Jul 01}, pages = {W308-14}, abstract = {

Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org.

}, keywords = {Computer Graphics, Dose-Response Relationship, Drug, Gene Expression Profiling, Internet, Kinetics, Oligonucleotide Array Sequence Analysis, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkn303}, author = {T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Huerta-Cepas, Jaime and Minguez, Pablo and Alloza, Eva and Al-Shahrour, F{\'a}tima and Vegas-Azc{\'a}rate, Susana and Goetz, Stefan and Escobar, Pablo and Garcia-Garcia, Francisco and Conesa, Ana and Montaner, David and Dopazo, Joaquin} } @article {595, title = {Interoperability with Moby 1.0--it{\textquoteright}s better than sharing your toothbrush!}, journal = {Brief Bioinform}, volume = {9}, year = {2008}, month = {2008 May}, pages = {220-31}, abstract = {

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

}, keywords = {Computational Biology, Database Management Systems, Databases, Factual, Information Storage and Retrieval, Internet, Programming Languages, Systems Integration}, issn = {1477-4054}, doi = {10.1093/bib/bbn003}, author = {Wilkinson, Mark D and Senger, Martin and Kawas, Edward and Bruskiewich, Richard and Gouzy, Jerome and Noirot, Celine and Bardou, Philippe and Ng, Ambrose and Haase, Dirk and Saiz, Enrique de Andres and Wang, Dennis and Gibbons, Frank and Gordon, Paul M K and Sensen, Christoph W and Carrasco, Jose Manuel Rodriguez and Fern{\'a}ndez, Jos{\'e} M and Shen, Lixin and Links, Matthew and Ng, Michael and Opushneva, Nina and Neerincx, Pieter B T and Leunissen, Jack A M and Ernst, Rebecca and Twigger, Simon and Usadel, Bjorn and Good, Benjamin and Wong, Yan and Stein, Lincoln and Crosby, William and Karlsson, Johan and Royo, Romina and P{\'a}rraga, Iv{\'a}n and Ram{\'\i}rez, Sergio and Gelpi, Josep Lluis and Trelles, Oswaldo and Pisano, David G and Jimenez, Natalia and Kerhornou, Arnaud and Rosset, Roman and Zamacola, Leire and T{\'a}rraga, Joaqu{\'\i}n and Huerta-Cepas, Jaime and Carazo, Jose Mar{\'\i}a and Dopazo, Joaquin and Guig{\'o}, Roderic and Navarro, Arcadi and Orozco, Modesto and Valencia, Alfonso and Claros, M Gonzalo and P{\'e}rez, Antonio J and Aldana, Jose and Rojano, M Mar and Fernandez-Santa Cruz, Raul and Navas, Ismael and Schiltz, Gary and Farmer, Andrew and Gessler, Damian and Schoof, Heiko and Groscurth, Andreas} } @article {598, title = {PhylomeDB: a database for genome-wide collections of gene phylogenies.}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, month = {2008 Jan}, pages = {D491-6}, abstract = {

The complete collection of evolutionary histories of all genes in a genome, also known as phylome, constitutes a valuable source of information. The reconstruction of phylomes has been previously prevented by large demands of time and computer power, but is now feasible thanks to recent developments in computers and algorithms. To provide a publicly available repository of complete phylomes that allows researchers to access and store large-scale phylogenomic analyses, we have developed PhylomeDB. PhylomeDB is a database of complete phylomes derived for different genomes within a specific taxonomic range. All phylomes in the database are built using a high-quality phylogenetic pipeline that includes evolutionary model testing and alignment trimming phases. For each genome, PhylomeDB provides the alignments, phylogentic trees and tree-based orthology predictions for every single encoded protein. The current version of PhylomeDB includes the phylomes of Human, the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli, comprising a total of 32 289 seed sequences with their corresponding alignments and 172 324 phylogenetic trees. PhylomeDB can be publicly accessed at http://phylomedb.bioinfo.cipf.es.

}, keywords = {Base Sequence, Escherichia coli, Genes, Genomics, History, Ancient, Humans, Phylogeny, Proteins, Saccharomyces cerevisiae, Sequence Alignment}, issn = {1362-4962}, doi = {10.1093/nar/gkm899}, author = {Huerta-Cepas, Jaime and Bueno, Anibal and Dopazo, Joaquin and Gabald{\'o}n, Toni} } @article {604, title = {Evidence for systems-level molecular mechanisms of tumorigenesis.}, journal = {BMC Genomics}, volume = {8}, year = {2007}, month = {2007 Jun 20}, pages = {185}, abstract = {

BACKGROUND: Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth.

RESULTS: Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis.

CONCLUSION: Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

}, keywords = {Cell Transformation, Neoplastic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, Male, Models, Biological, Models, Genetic, Models, Statistical, Neoplasm Proteins, Neoplasms, Prostatic Neoplasms, Protein Interaction Mapping, RNA, Messenger, Signal Transduction, Systems biology}, issn = {1471-2164}, doi = {10.1186/1471-2164-8-185}, author = {Hern{\'a}ndez, Pilar and Huerta-Cepas, Jaime and Montaner, David and Al-Shahrour, F{\'a}tima and Valls, Joan and G{\'o}mez, Laia and Capell{\`a}, Gabriel and Dopazo, Joaquin and Pujana, Miguel Angel} } @article {606, title = {From genes to functional classes in the study of biological systems.}, journal = {BMC Bioinformatics}, volume = {8}, year = {2007}, month = {2007 Apr 03}, pages = {114}, abstract = {

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.

}, keywords = {Algorithms, Chromosome Mapping, Computer Simulation, Gene Expression Profiling, Models, Biological, Multigene Family, Signal Transduction, Software, Systems biology, User-Computer Interface}, issn = {1471-2105}, doi = {10.1186/1471-2105-8-114}, author = {Al-Shahrour, F{\'a}tima and Arbiza, Leonardo and Dopazo, Hern{\'a}n and Huerta-Cepas, Jaime and Minguez, Pablo and Montaner, David and Dopazo, Joaquin} }