@inbook {684, title = {Protein Interactions for Functional Genomics}, booktitle = {Biological Data Mining in Protein Interaction Networks}, year = {2009}, pages = {223-238}, publisher = {Idea Group Inc (IGI)}, organization = {Idea Group Inc (IGI)}, address = {Hershey, USA}, issn = {1605663980, 978160566398}, url = {http://books.google.es/books?id=pNyCy5GsqtkC}, author = {Minguez, P. and Dopazo, J.}, editor = {Li, Xiao-Li and Ng, See-Kiong} } @article {18515841, title = {Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, note = {

Al-Shahrour, Fatima Carbonell, Jose Minguez, Pablo Goetz, Stefan Conesa, Ana Tarraga, Joaquin Medina, Ignacio Alloza, Eva Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W341-6. Epub 2008 May 31.

}, pages = {W341-6}, abstract = {

We present a new version of Babelomics, a complete suite of web tools for the functional profiling of genome scale experiments, with new and improved methods as well as more types of functional definitions. Babelomics includes different flavours of conventional functional enrichment methods as well as more advanced gene set analysis methods that makes it a unique tool among the similar resources available. In addition to the well-known functional definitions (GO, KEGG), Babelomics includes new ones such as Biocarta pathways or text mining-derived functional terms. Regulatory modules implemented include transcriptional control (Transfac, CisRed) and other levels of regulation such as miRNA-mediated interference. Moreover, Babelomics allows for sub-selection of terms in order to test more focused hypothesis. Also gene annotation correspondence tables can be imported, which allows testing with user-defined functional modules. Finally, a tool for the {\textquoteright}de novo{\textquoteright} functional annotation of sequences has been included in the system. This allows using yet unannotated organisms in the program. Babelomics has been extensively re-engineered and now it 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. Babelomics is available at http://www.babelomics.org.

}, keywords = {babelomics, funtional profiling}, url = {http://nar.oxfordjournals.org/content/36/suppl_2/W341.long}, author = {Fatima Al-Shahrour and Carbonell, J. and Minguez, P. and Goetz, S. and A. Conesa and Tarraga, J. and Medina, Ignacio and Alloza, E. and Montaner, D. and Dopazo, J.} } @article {18697870, title = {Controlled ovarian stimulation induces a functional genomic delay of the endometrium with potential clinical implications}, journal = {J Clin Endocrinol Metab}, volume = {93}, number = {11}, year = {2008}, note = {

Horcajadas, Jose A Minguez, Pablo Dopazo, Joaquin Esteban, Francisco J Dominguez, Francisco Giudice, Linda C Pellicer, Antonio Simon, Carlos Research Support, Non-U.S. Gov{\textquoteright}t United States The Journal of clinical endocrinology and metabolism J Clin Endocrinol Metab. 2008 Nov;93(11):4500-10. Epub 2008 Aug 12.

}, pages = {4500-10}, abstract = {

CONTEXT: Controlled ovarian stimulation induces morphological, biochemical, and functional genomic modifications of the human endometrium during the window of implantation. OBJECTIVE: Our objective was to compare the gene expression profile of the human endometrium in natural vs. controlled ovarian stimulation cycles throughout the early-mid secretory transition using microarray technology. METHOD: Microarray data from 49 endometrial biopsies obtained from LH+1 to LH+9 (n=25) in natural cycles and from human chorionic gonadotropin (hCG) +1 to hCG+9 in controlled ovarian stimulation cycles (n=24) were analyzed using different methods, such as clustering, profiling of biological processes, and selection of differentially expressed genes, as implemented in Gene Expression Pattern Analysis Suite and Babelomics programs. RESULTS: Endometria from natural cycles followed different genomic patterns compared with controlled ovarian stimulation cycles in the transition from the pre-receptive (days LH/hCG+1 until LH/hCG+5) to the receptive phase (day LH+7/hCG+7). Specifically, we have demonstrated the existence of a 2-d delay in the activation/repression of two clusters composed by 218 and 133 genes, respectively, on day hCG+7 vs. LH+7. Many of these delayed genes belong to the class window of implantation genes affecting basic biological processes in the receptive endometrium. CONCLUSIONS: These results demonstrate that gene expression profiling of the endometrium is different between natural and controlled ovarian stimulation cycles in the receptive phase. Identification of these differentially regulated genes can be used to understand the different developmental profiles of receptive endometrium during controlled ovarian stimulation and to search for the best controlled ovarian stimulation treatment in terms of minimal endometrial impact.

}, keywords = {Algorithms Chorionic Gonadotropin/genetics Endometrium/cytology/pathology/*physiology/physiopathology Female Gene Expression Regulation Genome, Human Glutathione Peroxidase/genetics Humans Insulin-Like Growth Factor Binding Proteins/genetics Luteal Phase/physiology Luteinizing Hormone/genetics Menstrual Cycle Oligonucleotide Array Sequence Analysis Ovulation Induction/*methods RNA/genetics/isola}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18697870}, author = {Horcajadas, J. A. and Minguez, P. and Dopazo, J. and Esteban, F. J. and Dominguez, F. and Giudice, L. C. and Pellicer, A. and Simon, C.} } @article {18508806, title = {GEPAS, a web-based tool for microarray data analysis and interpretation}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, note = {

Tarraga, Joaquin Medina, Ignacio Carbonell, Jose Huerta-Cepas, Jaime Minguez, Pablo Alloza, Eva Al-Shahrour, Fatima Vegas-Azcarate, Susana Goetz, Stefan Escobar, Pablo Garcia-Garcia, Francisco Conesa, Ana Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W308-14. Epub 2008 May 28.

}, 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 = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18508806}, author = {Tarraga, J. and Medina, Ignacio and Carbonell, J. and Huerta-Cepas, J. and Minguez, P. and Alloza, E. and Fatima Al-Shahrour and Vegas-Azcarate, S. and Goetz, S. and Escobar, P. and Garcia-Garcia, F. and A. Conesa and Montaner, D. and Dopazo, J.} } @article {17478504, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments}, journal = {Nucleic Acids Res}, volume = {35}, number = {Web Server issue}, year = {2007}, note = {

Al-Shahrour, Fatima Minguez, Pablo Tarraga, Joaquin Medina, Ignacio Alloza, Eva Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W91-6. Epub 2007 May 3.

}, pages = {W91-6}, abstract = {

The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.

}, keywords = {babelomics, functional enrichment analysys}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17478504}, author = {Fatima Al-Shahrour and Minguez, P. and Tarraga, J. and Medina, Ignacio and Alloza, E. and Montaner, D. and Dopazo, J.} } @article {17407596, title = {From genes to functional classes in the study of biological systems}, journal = {BMC Bioinformatics}, volume = {8}, year = {2007}, note = {

Al-Shahrour, Fatima Arbiza, Leonardo Dopazo, Hernan Huerta-Cepas, Jaime Minguez, Pablo Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England BMC bioinformatics BMC Bioinformatics. 2007 Apr 3;8:114.

}, 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/*methods Computer Simulation Gene Expression Profiling/methods *Models, babelomics, Biological Multigene Family/*physiology Signal Transduction/*physiology *Software Systems Biology/*methods *User-Computer Interface}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17407596}, author = {Fatima Al-Shahrour and Arbiza, L. and H. Dopazo and Huerta-Cepas, J. and Minguez, P. and Montaner, D. and Dopazo, J.} } @article {17855415, title = {Functional profiling of microarray experiments using text-mining derived bioentities}, journal = {Bioinformatics}, volume = {23}, number = {22}, year = {2007}, note = {

Minguez, Pablo Al-Shahrour, Fatima Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Bioinformatics (Oxford, England) Bioinformatics. 2007 Nov 15;23(22):3098-9. Epub 2007 Sep 13.

}, pages = {3098-9}, abstract = {

MOTIVATION: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

}, keywords = {Artificial Intelligence *Databases, babelomics, Protein Gene Expression Profiling/*methods Information Storage and Retrieval/*methods *Natural Language Processing Proteins/*classification/*metabolism Research/*methods Systems Integration}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17855415}, author = {Minguez, P. and Fatima Al-Shahrour and Montaner, D. and Dopazo, J.} } @article {16845052, title = {BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments}, journal = {Nucleic Acids Res}, volume = {34}, year = {2006}, note = {

Al-Shahrour, Fatima Minguez, Pablo Tarraga, Joaquin Montaner, David Alloza, Eva Vaquerizas, Juan M Conde, Lucia Blaschke, Christian Vera, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W472-6.

}, pages = {W472-6}, abstract = {

We present a new version of Babelomics, a complete suite of web tools for functional analysis of genome-scale experiments, with new and improved tools. New functionally relevant terms have been included such as CisRed motifs or bioentities obtained by text-mining procedures. An improved indexing has considerably speeded up several of the modules. An improved version of the FatiScan method for studying the coordinate behaviour of groups of functionally related genes is presented, along with a similar tool, the Gene Set Enrichment Analysis. Babelomics is now more oriented to test systems biology inspired hypotheses. Babelomics can be found at http://www.babelomics.org.

}, keywords = {babelomics, functional profiling}, url = {http://nar.oxfordjournals.org/content/34/suppl_2/W472.long}, author = {Fatima Al-Shahrour and Minguez, P. and Tarraga, J. and Montaner, D. and Alloza, E. and Vaquerizas, J. M. and L. Conde and Blaschke, C. and Vera, J. and Dopazo, J.} } @article {17503379, title = {A function-centric approach to the biological interpretation of microarray time-series}, journal = {Genome Inform}, volume = {17}, number = {2}, year = {2006}, note = {

Minguez, Pablo Al-Shahrour, Fatima Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t Japan Genome informatics. International Conference on Genome Informatics Genome Inform. 2006;17(2):57-66.

}, pages = {57-66}, abstract = {

The interpretation of microarray experiments is commonly addressed by means a two-step approach in which the relevant genes are firstly selected uniquely on the basis of their experimental values (ignoring their coordinate behaviors) and in a second step their functional properties are studied to hypothesize about the biological roles they are fulfilling in the cell. Recently, different methods (e.g. GSEA or FatiScan) have been proposed to study the coordinate behavior of blocks of functionally-related genes. These methods study the distribution of functional information across lists of genes ranked according their different experimental values in a static situation, such as the comparison between two classes (e.g. healthy controls versus diseased cases). Nevertheless there is no an equivalent way of studying a dynamic situation from a functional point of view. We present a method for the functional analysis of microarrays series in which the experiments display autocorrelation between successive points (e.g. time series, dose-response experiments, etc.) The method allows to recover the dynamics of the molecular roles fulfilled by the genes along the series which provides a novel approach to functional interpretation of such experiments. The method finds blocks of functionally-related genes which are significantly and coordinately over-expressed at different points of the series. This method draws inspiration from systems biology given that the analysis does not focus on individual properties of genes but on collective behaving blocks of functionally-related genes. The FatiScan algorithm used in the method proposed is available at: http://fatiscan.bioinfo.cipf.es, or within the Babelomics suite: http://www.babelomics.org. Additional material is available at: http://bioinfo.cipf.es/data/plasmodium.

}, keywords = {babelomics}, author = {Minguez, P. and Fatima Al-Shahrour and Dopazo, J.} } @article {16845056, title = {Next station in microarray data analysis: GEPAS}, journal = {Nucleic Acids Res}, volume = {34}, year = {2006}, note = {

Montaner, David Tarraga, Joaquin Huerta-Cepas, Jaime Burguet, Jordi Vaquerizas, Juan M Conde, Lucia Minguez, Pablo Vera, Javier Mukherjee, Sach Valls, Joan Pujana, Miguel A G Alloza, Eva Herrero, Javier Al-Shahrour, Fatima Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W486-91.

}, pages = {W486-91}, abstract = {

The Gene Expression Profile Analysis Suite (GEPAS) has been running for more than four years. During this time it has evolved to keep pace with the new interests and trends in the still changing world of microarray data analysis. GEPAS has been designed to provide an intuitive although powerful web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-colour microarray experiments and other preprocessing options), to the final step of the functional annotation of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), and include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management. GEPAS is extensively used by researchers of many countries and its records indicate an average usage rate of 400 experiments per day. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

}, keywords = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16845056}, author = {Montaner, D. and Tarraga, J. and Huerta-Cepas, J. and Burguet, J. and Vaquerizas, J. M. and L. Conde and Minguez, P. and Vera, J. and Mukherjee, S. and Valls, J. and Pujana, M. A. and Alloza, E. and Herrero, J. and Fatima Al-Shahrour and Dopazo, J.} } @article {15980512, title = {BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments}, journal = {Nucleic Acids Res}, volume = {33}, year = {2005}, note = {

Al-Shahrour, Fatima Minguez, Pablo Vaquerizas, Juan M Conde, Lucia Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W460-4.

}, pages = {W460-4}, abstract = {

We present Babelomics, a complete suite of web tools for the functional analysis of groups of genes in high-throughput experiments, which includes the use of information on Gene Ontology terms, interpro motifs, KEGG pathways, Swiss-Prot keywords, analysis of predicted transcription factor binding sites, chromosomal positions and presence in tissues with determined histological characteristics, through five integrated modules: FatiGO (fast assignment and transference of information), FatiWise, transcription factor association test, GenomeGO and tissues mining tool, respectively. Additionally, another module, FatiScan, provides a new procedure that integrates biological information in combination with experimental results in order to find groups of genes with modest but coordinate significant differential behaviour. FatiScan is highly sensitive and is capable of finding significant asymmetries in the distribution of genes of common function across a list of ordered genes even if these asymmetries were not extreme. The strong multiple-testing nature of the contrasts made by the tools is taken into account. All the tools are integrated in the gene expression analysis package GEPAS. Babelomics is the natural evolution of our tool FatiGO (which analysed almost 22,000 experiments during the last year) to include more sources on information and new modes of using it. Babelomics can be found at http://www.babelomics.org.

}, keywords = {babelomics, functional profiling}, url = {http://nar.oxfordjournals.org/content/33/suppl_2/W460.long}, author = {Fatima Al-Shahrour and Minguez, P. and Vaquerizas, J. M. and L. Conde and Dopazo, J.} } @article {15980548, title = {GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data}, journal = {Nucleic Acids Res}, volume = {33}, year = {2005}, note = {

Vaquerizas, Juan M Conde, Lucia Yankilevich, Patricio Cabezon, Amaya Minguez, Pablo Diaz-Uriarte, Ramon Al-Shahrour, Fatima Herrero, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W616-20.

}, pages = {W616-20}, abstract = {

The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With \>76,000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

}, keywords = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15980548}, author = {Vaquerizas, J. M. and L. Conde and Yankilevich, P. and Cabezon, A. and Minguez, P. and Diaz-Uriarte, R. and Fatima Al-Shahrour and Herrero, J. and Dopazo, J.} }