@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.} } @inbook {478, title = {Functional annotation of microarray experiments}, booktitle = {Microarray Technology Through Applications}, year = {2007}, publisher = {Taylor \& Francis, F. Falciani}, organization = {Taylor \& Francis, F. Falciani}, address = {New York, USA}, author = {Dopazo, J. and Fatima Al-Shahrour} } @article {17597935, title = {Functional profiling and gene expression analysis of chromosomal copy number alterations}, journal = {Bioinformation}, volume = {1}, number = {10}, year = {2007}, note = {

Conde, Lucia Montaner, David Burguet-Castell, Jordi Tarraga, Joaquin Al-Shahrour, Fatima Dopazo, Joaquin Singapore Bioinformation Bioinformation. 2007 Apr 10;1(10):432-5.

}, pages = {432-5}, abstract = {

Contrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.

}, keywords = {babelomics}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17597935}, author = {L. Conde and Montaner, D. and Burguet-Castell, J. and Tarraga, J. and Fatima Al-Shahrour 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 {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 {14990455, title = {FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes}, journal = {Bioinformatics}, volume = {20}, number = {4}, year = {2004}, note = {

Al-Shahrour, Fatima Diaz-Uriarte, Ramon Dopazo, Joaquin England Bioinformatics (Oxford, England) Bioinformatics. 2004 Mar 1;20(4):578-80. Epub 2004 Jan 22.

}, pages = {578-80}, abstract = {

We present a simple but powerful procedure to extract Gene Ontology (GO) terms that are significantly over- or under-represented in sets of genes within the context of a genome-scale experiment (DNA microarray, proteomics, etc.). Said procedure has been implemented as a web application, FatiGO, allowing for easy and interactive querying. FatiGO, which takes the multiple-testing nature of statistical contrast into account, currently includes GO associations for diverse organisms (human, mouse, fly, worm and yeast) and the TrEMBL/Swissprot GOAnnotations@EBI correspondences from the European Bioinformatics Institute.

}, keywords = {*Algorithms Artificial Intelligence Databases, babelomics, DNA/*methods *Software, Genetic Gene Expression Profiling/*methods *Hypermedia Information Storage and Retrieval/*methods *Internet *Phylogeny Sequence Alignment/methods Sequence Analysis}, url = {http://bioinformatics.oxfordjournals.org/content/20/4/578.abstract}, author = {Fatima Al-Shahrour and Diaz-Uriarte, R. and Dopazo, J.} }