Integrated gene set analysis for microRNA studies. - Garcia-Garcia, Francisco; Panadero, Joaquin; Dopazo, Joaquin; Montaner, David (Bioinformatics, 2016)
MOTIVATION: Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limitations of this approach have already been described at the gene level, while some newer arise in the miRNA scenario.Here, we propose an enhanced methodology that builds on the well-established gene set analysis paradigm. Evidence for differential expression at the miRNA level is transferred to a gene differential inhibition score which is easily interpretable in terms of gene sets or pathways. Such transferred indexes account for the additive effect of several miRNAs targeting the same gene, and also incorporate cancellation effects between cases and controls. Together, these two desirable characteristics allow for more accurate modeling of regulatory processes. RESULTS: We analyze high-throughput sequencing data from 20 different cancer types and provide exhaustive reports of gene and Gene Ontology-term deregulation by miRNA action. AVAILABILITY AND IMPLEMENTATION: The proposed methodology was implemented in the Bioconductor library mdgsa http://bioconductor.org/packages/mdgsa For the purpose of reproducibility all of the scripts are available at https://github.com/dmontaner-papers/gsa4mirna CONTACT: : david.montaner@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Keywords: Computational Biology; Gene Expression Profiling; Gene ontology; Gene Regulatory Networks; High-Throughput Nucleotide Sequencing; Humans; MicroRNAs; Neoplasms; Reproducibility of Results

Defining the genomic signature of totipotency and pluripotency during early human development. - Galan, Amparo; Diaz-Gimeno, Patricia; Poo, Maria Eugenia; Valbuena, Diana; Sanchez, Eva; Ruiz, Veronica; Dopazo, Joaquin; Montaner, David; Conesa, Ana; Simon, Carlos (PLoS One, 2013)
The genetic mechanisms governing human pre-implantation embryo development and the in vitro counterparts, human embryonic stem cells (hESCs), still remain incomplete. Previous global genome studies demonstrated that totipotent blastomeres from day-3 human embryos and pluripotent inner cell masses (ICMs) from blastocysts, display unique and differing transcriptomes. Nevertheless, comparative gene expression analysis has revealed that no significant differences exist between hESCs derived from blastomeres versus those obtained from ICMs, suggesting that pluripotent hESCs involve a new developmental progression. To understand early human stages evolution, we developed an undifferentiation network signature (UNS) and applied it to a differential gene expression profile between single blastomeres from day-3 embryos, ICMs and hESCs. This allowed us to establish a unique signature composed of highly interconnected genes characteristic of totipotency (61 genes), in vivo pluripotency (20 genes), and in vitro pluripotency (107 genes), and which are also proprietary according to functional analysis. This systems biology approach has led to an improved understanding of the molecular and signaling processes governing human pre-implantation embryo development, as well as enabling us to comprehend how hESCs might adapt to in vitro culture conditions.
Keywords: Blastocyst Inner Cell Mass; Blastomeres; Cell Differentiation; Embryonic Development; Embryonic Stem Cells; Gene Expression Profiling; Gene Regulatory Networks; Genome, Human; Humans; Molecular Sequence Annotation; Pluripotent Stem Cells; Totipotent Stem Cells

Extensive translatome remodeling during ER stress response in mammalian cells. - Ventoso, Iván; Kochetov, Alex; Montaner, David; Dopazo, Joaquin; Santoyo, Javier (PLoS One, 2012)
In this work we have described the translatome of two mammalian cell lines, NIH3T3 and Jurkat, by scoring the relative polysome association of ∼10,000 mRNA under normal and ER stress conditions. We have found that translation efficiencies of mRNA correlated poorly with transcript abundance, although a general tendency was observed so that the highest translation efficiencies were found in abundant mRNA. Despite the differences found between mouse (NIH3T3) and human (Jurkat) cells, both cell types share a common translatome composed by ∼800-900 mRNA that encode proteins involved in basic cellular functions. Upon stress, an extensive remodeling in translatomes was observed so that translation of ∼50% of mRNA was inhibited in both cell types, this effect being more dramatic for those mRNA that accounted for most of the cell translation. Interestingly, we found two subsets comprising 1000-1500 mRNA whose translation resisted or was induced by stress. Translation arrest resistant class includes many mRNA encoding aminoacyl tRNA synthetases, ATPases and enzymes involved in DNA replication and stress response such as BiP. This class of mRNA is characterized by high translation rates in both control and stress conditions. Translation inducible class includes mRNA whose translation was relieved after stress, showing a high enrichment in early response transcription factors of bZIP and zinc finger C2H2 classes. Unlike yeast, a general coordination between changes in translation and transcription upon stress (potentiation) was not observed in mammalian cells. Among the different features of mRNA analyzed, we found a relevant association of translation efficiency with the presence of upstream ATG in the 5'UTR and with the length of coding sequence of mRNA, and a looser association with other parameters such as the length and the G+C content of 5'UTR. A model for translatome remodeling during the acute phase of stress response in mammalian cells is proposed.
Keywords: Animals; Endoplasmic Reticulum Stress; Humans; Jurkat Cells; Mice; NIH 3T3 Cells; Oligonucleotide Array Sequence Analysis; Protein Biosynthesis; RNA, Messenger; Transcription, Genetic

Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease. - Fernández, Raquel Ma; Bleda, Marta; Núñez-Torres, Rocío; Medina, Ignacio; Luzón-Toro, Berta; García-Alonso, Luz; Torroglosa, Ana; Marbà, Martina; Enguix-Riego, Ma Valle; Montaner, David; Antiňolo, Guillermo; Dopazo, Joaquin; et al. (Orphanet J Rare Dis, 2012)
Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung's disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.
Keywords: Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Genotype; Hirschsprung Disease; Humans; Male

Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells. - Yung, Sun; Ledran, Maria; Moreno-Gimeno, Inmaculada; Conesa, Ana; Montaner, David; Dopazo, Joaquin; Dimmick, Ian; Slater, Nicholas J; Marenah, Lamin; Real, Pedro J; Paraskevopoulou, Iliana; Bisbal, Viviana; et al. (Hum Mol Genet, 2011)
Understanding the transcriptional cues that direct differentiation of human embryonic stem cells (hESCs) and human-induced pluripotent stem cells to defined and functional cell types is essential for future clinical applications. In this study, we have compared transcriptional profiles of haematopoietic progenitors derived from hESCs at various developmental stages of a feeder- and serum-free differentiation method and show that the largest transcriptional changes occur during the first 4 days of differentiation. Data mining on the basis of molecular function revealed Rho-GTPase signalling as a key regulator of differentiation. Inhibition of this pathway resulted in a significant reduction in the numbers of emerging haematopoietic progenitors throughout the differentiation window, thereby uncovering a previously unappreciated role for Rho-GTPase signalling during human haematopoietic development. Our analysis indicated that SCL was the 11th most upregulated transcript during the first 4 days of the hESC differentiation process. Overexpression of SCL in hESCs promoted differentiation to meso-endodermal lineages, the emergence of haematopoietic and erythro-megakaryocytic progenitors and accelerated erythroid differentiation. Importantly, intrasplenic transplantation of SCL-overexpressing hESC-derived haematopoietic cells enhanced recovery from induced acute anaemia without significant cell engraftment, suggesting a paracrine-mediated effect.
Keywords: Acute Disease; Anemia, Hemolytic; Animals; Basic Helix-Loop-Helix Transcription Factors; Cell Differentiation; Cell Line; Cell Lineage; Cluster Analysis; Embryonic Stem Cells; Erythroid Cells; Flow Cytometry; Gene Expression Profiling; Hematopoietic Stem Cells; Humans; Mice; Myeloid Cells; Paracrine Communication; Proto-Oncogene Proteins; Reverse Transcriptase Polymerase Chain Reaction; rho GTP-Binding Proteins; Signal Transduction; Stem Cell Transplantation; T-Cell Acute Lymphocytic Leukemia Protein 1; Transcriptome

DNA methylation epigenotypes in breast cancer molecular subtypes. - Bediaga, Naiara G; Acha-Sagredo, Amelia; Guerra, Isabel; Viguri, Amparo; Albaina, Carmen; Ruiz Diaz, Irune; Rezola, Ricardo; Alberdi, Maria Jesus; Dopazo, Joaquin; Montaner, David; Renobales, Mertxe; Fernandez, Agustin F; et al. (Breast Cancer Res, 2010)
INTRODUCTION: Identification of gene expression based breast cancer subtypes is considered as a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and there is only a limited understanding of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and deliver specific epigenotypes associated with particular breast cancer subtypes. METHODS: Using a microarray approach we analyzed DNA methylation in regulatory regions of 806 cancer related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biological validation by Pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A and 48 luminal B paired breast cancer/adjacent tissues. Using all-subset selection method, we identified the most subtype predictive methylation profiles in multivariable logistic regression analysis. RESULTS: The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identify novel subtype specific epigenotypes which clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors. CONCLUSIONS: Our results provide evidence that well defined DNA methylation profiles enables breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.
Keywords: Aged; Breast Neoplasms; CpG Islands; DNA Methylation; Epigenesis, Genetic; Female; Gene Expression Profiling; Genes, p53; Genotype; Humans; Ki-67 Antigen; Middle Aged; mutation; Neoplasm Grading; Oligonucleotide Array Sequence Analysis; Receptor, ErbB-2; Tumor Suppressor Protein p53

Functional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis. - Galan, Amparo; Montaner, David; Póo, M Eugenia; Valbuena, Diana; Ruiz, Veronica; Aguilar, Cristóbal; Dopazo, Joaquin; Simon, Carlos (PLoS One, 2010)
Blastomere fate and embryonic genome activation (EGA) during human embryonic development are unsolved areas of high scientific and clinical interest. Forty-nine blastomeres from 5- to 8-cell human embryos have been investigated following an efficient single-cell cDNA amplification protocol to provide a template for high-density microarray analysis. The previously described markers, characteristic of Inner Cell Mass (ICM) (n = 120), stemness (n = 190) and Trophectoderm (TE) (n = 45), were analyzed, and a housekeeping pattern of 46 genes was established. All the human blastomeres from the 5- to 8-cell stage embryo displayed a common gene expression pattern corresponding to ICM markers (e.g., DDX3, FOXD3, LEFTY1, MYC, NANOG, POU5F1), stemness (e.g., POU5F1, DNMT3B, GABRB3, SOX2, ZFP42, TERT), and TE markers (e.g., GATA6, EOMES, CDX2, LHCGR). The EGA profile was also investigated between the 5-6- and 8-cell stage embryos, and compared to the blastocyst stage. Known genes (n = 92) such as depleted maternal transcripts (e.g., CCNA1, CCNB1, DPPA2) and embryo-specific activation (e.g., POU5F1, CDH1, DPPA4), as well as novel genes, were confirmed. In summary, the global single-cell cDNA amplification microarray analysis of the 5- to 8-cell stage human embryos reveals that blastomere fate is not committed to ICM or TE. Finally, new EGA features in human embryogenesis are presented.
Keywords: Blastomeres; DNA, Complementary; Gene Expression Profiling; Genomics; Humans; Oligonucleotide Array Sequence Analysis

Hypoxia promotes efficient differentiation of human embryonic stem cells to functional endothelium. - Prado-Lopez, Sonia; Conesa, Ana; Armiñán, Ana; Martínez-Losa, Magdalena; Escobedo-Lucea, Carmen; Gandia, Carolina; Tarazona, Sonia; Melguizo, Dario; Blesa, David; Montaner, David; Sanz-González, Silvia; Sepúlveda, Pilar; et al. (Stem Cells, 2010)
Early development of mammalian embryos occurs in an environment of relative hypoxia. Nevertheless, human embryonic stem cells (hESC), which are derived from the inner cell mass of blastocyst, are routinely cultured under the same atmospheric conditions (21% O(2)) as somatic cells. We hypothesized that O(2) levels modulate gene expression and differentiation potential of hESC, and thus, we performed gene profiling of hESC maintained under normoxic or hypoxic (1% or 5% O(2)) conditions. Our analysis revealed that hypoxia downregulates expression of pluripotency markers in hESC but increases significantly the expression of genes associated with angio- and vasculogenesis including vascular endothelial growth factor and angiopoitein-like proteins. Consequently, we were able to efficiently differentiate hESC to functional endothelial cells (EC) by varying O(2) levels; after 24 hours at 5% O(2), more than 50% of cells were CD34+. Transplantation of resulting endothelial-like cells improved both systolic function and fractional shortening in a rodent model of myocardial infarction. Moreover, analysis of the infarcted zone revealed that transplanted EC reduced the area of fibrous scar tissue by 50%. Thus, use of hypoxic conditions to specify the endothelial lineage suggests a novel strategy for cellular therapies aimed at repair of damaged vasculature in pathologies such as cerebral ischemia and myocardial infarction.
Keywords: Angiopoietin-1; Animals; biomarkers; Cell Culture Techniques; Cell Differentiation; Cell Hypoxia; Cell Transplantation; Cells, Cultured; Down-Regulation; Embryonic Stem Cells; Endothelial Cells; Gene Expression Profiling; Gene Expression Regulation; Humans; Male; Myocardial Infarction; Neovascularization, Physiologic; Oxygen; Pluripotent Stem Cells; Rats; Rats, Nude; Vascular Endothelial Growth Factor A

Multidimensional gene set analysis of genomic data. - Montaner, David; Dopazo, Joaquin (PLoS One, 2010)
Understanding the functional implications of changes in gene expression, mutations, etc., is the aim of most genomic experiments. To achieve this, several functional profiling methods have been proposed. Such methods study the behaviour of different gene modules (e.g. gene ontology terms) in response to one particular variable (e.g. differential gene expression). In spite to the wealth of information provided by functional profiling methods, a common limitation to all of them is their inherent unidimensional nature. In order to overcome this restriction we present a multidimensional logistic model that allows studying the relationship of gene modules with different genome-scale measurements (e.g. differential expression, genotyping association, methylation, copy number alterations, heterozygosity, etc.) simultaneously. Moreover, the relationship of such functional modules with the interactions among the variables can also be studied, which produces novel results impossible to be derived from the conventional unidimensional functional profiling methods. We report sound results of gene sets associations that remained undetected by the conventional one-dimensional gene set analysis in several examples. Our findings demonstrate the potential of the proposed approach for the discovery of new cell functionalities with complex dependences on more than one variable.
Keywords: Databases, Genetic; Gene Expression Profiling; Gene Regulatory Networks; Genome, Human; Genomics; Humans; Models, Statistical

Gene set internal coherence in the context of functional profiling. - Montaner, David; Minguez, Pablo; Al-Shahrour, Fátima; Dopazo, Joaquin (BMC Genomics, 2009)
BACKGROUND: Functional profiling methods have been extensively used in the context of high-throughput experiments and, in particular, in microarray data analysis. Such methods use available biological information to define different types of functional gene modules (e.g. gene ontology -GO-, KEGG pathways, etc.) whose representation in a pre-defined list of genes is further studied. In the most popular type of microarray experimental designs (e.g. up- or down-regulated genes, clusters of co-expressing genes, etc.) or in other genomic experiments (e.g. Chip-on-chip, epigenomics, etc.) these lists are composed by genes with a high degree of co-expression. Therefore, an implicit assumption in the application of functional profiling methods within this context is that the genes corresponding to the modules tested are effectively defining sets of co-expressing genes. Nevertheless not all the functional modules are biologically coherent entities in terms of co-expression, which will eventually hinder its detection with conventional methods of functional enrichment. RESULTS: Using a large collection of microarray data we have carried out a detailed survey of internal correlation in GO terms and KEGG pathways, providing a coherence index to be used for measuring functional module co-regulation. An unexpected low level of internal correlation was found among the modules studied. Only around 30% of the modules defined by GO terms and 57% of the modules defined by KEGG pathways display an internal correlation higher than the expected by chance.This information on the internal correlation of the genes within the functional modules can be used in the context of a logistic regression model in a simple way to improve their detection in gene expression experiments. CONCLUSION: For the first time, an exhaustive study on the internal co-expression of the most popular functional categories has been carried out. Interestingly, the real level of coexpression within many of them is lower than expected (or even inexistent), which will preclude its detection by means of most conventional functional profiling methods. If the gene-to-function correlation information is used in functional profiling methods, the results obtained improve the ones obtained by conventional enrichment methods.
Keywords: Algorithms; Breast Neoplasms; Carcinoma, Intraductal, Noninfiltrating; Computational Biology; Databases, Nucleic Acid; Female; Gene Expression Profiling; Genomics; Humans; Oligonucleotide Array Sequence Analysis; Papillomavirus Infections; Reproducibility of Results

Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. - Medina, Ignacio; Montaner, David; Bonifaci, Núria; Pujana, Miguel Angel; Carbonell, José; Tárraga, Joaquín; Al-Shahrour, Fátima; Dopazo, Joaquin (Nucleic Acids Res, 2009)
Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.
Keywords: Biological Phenomena; Breast Neoplasms; Female; Genes; Genetic Variation; Genome-Wide Association Study; Humans; Polymorphism, Single Nucleotide; Software; User-Computer Interface

SNOW, a web-based tool for the statistical analysis of protein-protein interaction networks. - Minguez, Pablo; Götz, Stefan; Montaner, David; Al-Shahrour, Fátima; Dopazo, Joaquin (Nucleic Acids Res, 2009)
Understanding the structure and the dynamics of the complex intercellular network of interactions that contributes to the structure and function of a living cell is one of the main challenges of today's biology. SNOW inputs a collection of protein (or gene) identifiers and, by using the interactome as scaffold, draws the connections among them, calculates several relevant network parameters and, as a novelty among the rest of tools of its class, it estimates their statistical significance. The parameters calculated for each node are: connectivity, betweenness and clustering coefficient. It also calculates the number of components, number of bicomponents and articulation points. An interactive network viewer is also available to explore the resulting network. SNOW is available at http://snow.bioinfo.cipf.es.
Keywords: Computer Graphics; Data Interpretation, Statistical; Databases, Protein; Humans; Internet; Protein Interaction Mapping; Software

Direct functional assessment of the composite phenotype through multivariate projection strategies. - Conesa, Ana; Bro, Rasmus; Garcia-Garcia, Francisco; Prats, José Manuel; Götz, Stefan; Kjeldahl, Karin; Montaner, David; Dopazo, Joaquin (Genomics, 2008)
We present a novel approach for the analysis of transcriptomics data that integrates functional annotation of gene sets with expression values in a multivariate fashion, and directly assesses the relation of functional features to a multivariate space of response phenotypical variables. Multivariate projection methods are used to obtain new correlated variables for a set of genes that share a given function. These new functional variables are then related to the response variables of interest. The analysis of the principal directions of the multivariate regression allows for the identification of gene function features correlated with the phenotype. Two different transcriptomics studies are used to illustrate the statistical and interpretative aspects of the methodology. We demonstrate the superiority of the proposed method over equivalent approaches.
Keywords: Breast Neoplasms; Computational Biology; Databases, Genetic; Female; Gene Expression Profiling; Humans; Mathematical Computing; Multivariate Analysis; Phenotype

Evidence for systems-level molecular mechanisms of tumorigenesis. - Hernández, Pilar; Huerta-Cepas, Jaime; Montaner, David; Al-Shahrour, Fátima; Valls, Joan; Gómez, Laia; Capellà, Gabriel; Dopazo, Joaquin; Pujana, Miguel Angel (BMC Genomics, 2007)
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

FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. - Al-Shahrour, Fátima; Minguez, Pablo; Tárraga, Joaquín; Medina, Ignacio; Alloza, Eva; Montaner, David; Dopazo, Joaquin (Nucleic Acids Res, 2007)
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: Amino Acid Motifs; Animals; Binding Sites; Computational Biology; Gene Expression Profiling; Genes; Genomics; Humans; Internet; Oligonucleotide Array Sequence Analysis; Programming Languages; Software; Systems Integration; Transcription Factors

ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling. - Conde, Lucia; Montaner, David; Burguet-Castell, Jordi; Tárraga, Joaquín; Medina, Ignacio; Al-Shahrour, Fátima; Dopazo, Joaquin (Nucleic Acids Res, 2007)
We present the ISACGH, a web-based system that allows for the combination of genomic data with gene expression values and provides different options for functional profiling of the regions found. Several visualization options offer a convenient representation of the results. Different efficient methods for accurate estimation of genomic copy number from array-CGH hybridization data have been included in the program. Moreover, the connection to the gene expression analysis package GEPAS allows the use of different facilities for data pre-processing and analysis. A DAS server allows exporting the results to the Ensembl viewer where contextual genomic information can be obtained. The program is freely available at: http://isacgh.bioinfo.cipf.es or within http://www.gepas.org.
Keywords: Animals; Cluster Analysis; Computational Biology; Computer Graphics; Gene Expression Profiling; Humans; Internet; Models, Genetic; Nucleic Acid Hybridization; Oligonucleotide Array Sequence Analysis; Programming Languages; Software; Systems Integration; User-Computer Interface