@article {818, title = {A genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice.}, journal = {J Transl Med}, volume = {23}, year = {2025}, month = {2025 Jan 20}, pages = {86}, abstract = {

BACKGROUND: Despite the use of Next-Generation Sequencing (NGS) as the gold standard for the diagnosis of rare diseases, its clinical implementation has been challenging, limiting the cost-effectiveness of NGS and the understanding, control and safety essential for decision-making in clinical applications. Here, we describe a personalized NGS-based strategy integrating precision medicine into a public healthcare system and its implementation in the routine diagnosis process during a five-year pilot program.

METHODS: Our approach involved customized probe designs, the generation of virtual panels and the development of a personalized medicine module (PMM) for variant prioritization. This strategy was applied to 6500 individuals including 6267 index patients and 233 NGS-based carrier screenings.

RESULTS: Causative variants were identified in 2061 index patients (average 32.9\%, ranging from 12 to 62\% by condition). Also, 131 autosomal-recessive cases could be partially genetically diagnosed. These results led to over 5000 additional studies including carrier, prenatal and preimplantational tests or pharmacological and gene therapy treatments.

CONCLUSION: This strategy has shown promising improvements in the diagnostic rate, facilitating timely diagnosis and gradually expanding our services portfolio for rare diseases. The steps taken towards the integration of clinical and genomic data are opening new possibilities for conducting both retrospective and prospective healthcare studies. Overall, this study represents a major milestone in the ongoing efforts to improve our understanding and clinical management of rare diseases, a crucial area of medical research and care.

}, keywords = {Algorithms, Female, Genomics, High-Throughput Nucleotide Sequencing, Humans, Precision Medicine, rare diseases}, issn = {1479-5876}, doi = {10.1186/s12967-025-06069-2}, author = {M{\'e}ndez-Vidal, Cristina and Bravo-Gil, Nereida and Perez-Florido, Javier and Marcos-Luque, Irene and Fern{\'a}ndez, Raquel M and Fernandez-Rueda, Jose Luis and Gonz{\'a}lez-del Pozo, Mar{\'\i}a and Mart{\'\i}n-S{\'a}nchez, Marta and Fern{\'a}ndez-Su{\'a}rez, Elena and Mena, Marcela and Carmona, Rosario and Dopazo, Joaquin and Borrego, Salud and Anti{\v n}olo, Guillermo} } @article {811, title = {Genotypic characterization and antimicrobial susceptibility of human isolates in Southern Spain.}, journal = {Microbiol Spectr}, volume = {12}, year = {2024}, month = {2024 Oct 03}, pages = {e0102824}, abstract = {

is the main cause of bacterial gastroenteritis and a public health problem worldwide. Little information is available on the genotypic characteristics of human in Spain. This study is based on an analysis of the resistome, virulome, and phylogenetic relationship, antibiogram prediction, and antimicrobial susceptibility of 114 human isolates of from a tertiary hospital in southern Spain from October 2020 to June 2023. The isolates were sequenced using Illumina technology, and a bioinformatic analysis was subsequently performed. The susceptibility of isolates to ciprofloxacin, tetracycline, and erythromycin was also tested. The resistance rates for each antibiotic were 90.3\% for ciprofloxacin, 66.7\% for tetracycline, and 0.88\% for erythromycin. The fluoroquinolone resistance rate obtained is well above the European average (69.1\%). CC-21 ( = 23), ST-572 ( = 13), and ST-6532 ( = 13) were the most prevalent clonal complexes (CCs) and sequence types (STs). In the virulome, the , and genes were detected in all the isolates. A prevalence of 20.1\% was obtained for the genes and , which are related to the pathogenesis of Guillain-Barr{\'e} syndrome (GBS). The prevalence of the main antimicrobial resistance markers detected were CmeABC (92.1\%), RE-cmeABC (7.9\%), the T86I substitution in (88.9\%), (72.6\%) (65.8\%), and (17.1\%). High antibiogram prediction rates (>97\%) were obtained, except for in the case of the erythromycin-resistant phenotype. This study contributes significantly to the knowledge of genomics for the prevention, treatment, and control of infections caused by this pathogen.IMPORTANCEDespite being the pathogen with the greatest number of gastroenteritis cases worldwide, remains a poorly studied microorganism. A sustained increase in fluoroquinolone resistance in human isolates is a problem when treating infections. The development of whole genome sequencing (WGS) techniques has allowed us to better understand the genotypic characteristics of this pathogen and relate them to antibiotic resistance phenotypes. These techniques complement the data obtained from the phenotypic analysis of isolates. The zoonotic transmission of through the consumption of contaminated poultry supports approaching the study of this pathogen through "One Health" approach. In addition, due to the limited information on the genomic characteristics of in Spain, this study provides important data and allows us to compare the results with those obtained in other countries.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Anti-Bacterial Agents, Campylobacter Infections, Campylobacter jejuni, Child, Child, Preschool, Ciprofloxacin, Drug Resistance, Bacterial, Erythromycin, Female, Genotype, Humans, Infant, Male, Microbial Sensitivity Tests, Middle Aged, Phylogeny, Spain, Tetracycline, Young Adult}, issn = {2165-0497}, doi = {10.1128/spectrum.01028-24}, author = {Fern{\'a}ndez-Palacios, Pablo and Gal{\'a}n-S{\'a}nchez, F{\'a}tima and Casimiro-Soriguer, Carlos S and Jurado-Tarifa, Estefan{\'\i}a and Arroyo, Federico and Lara, Mar{\'\i}a and Chaves, J Alberto and Dopazo, Joaquin and Rodriguez-Iglesias, Manuel A} } @article {724, title = {Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data}, journal = {Computational and Structural Biotechnology Journal}, volume = {19}, year = {2021}, month = {Jan-01-2021}, pages = {2968 - 2978}, issn = {20010370}, doi = {10.1016/j.csbj.2021.05.022}, url = {https://linkinghub.elsevier.com/retrieve/pii/S2001037021002038}, author = {Rian, Kinza and Hidalgo, Marta R. and Cubuk, Cankut and Falco, Matias M. and Loucera, Carlos and Esteban-Medina, Marina and Alamo-Alvarez, Inmaculada and Pe{\~n}a-Chilet, Maria and Dopazo, Joaquin} } @article {717, title = {Genome-wide analysis of DNA methylation in Hirschsprung enteric precursor cells: unraveling the epigenetic landscape of enteric nervous system developmentAbstractBackgroundResultsConclusionsGraphic abstract}, journal = {Clinical Epigenetics}, volume = {13}, year = {2021}, month = {Jan-12-2021}, issn = {1868-7075}, doi = {10.1186/s13148-021-01040-6}, url = {http://link.springer.com/article/10.1186/s13148-021-01040-6/fulltext.html}, author = {Villalba-Benito, Leticia and L{\'o}pez-L{\'o}pez, Daniel and Torroglosa, Ana and Casimiro-Soriguer, Carlos S. and Luz{\'o}n-Toro, Berta and Fern{\'a}ndez, Raquel Mar{\'\i}a and Moya-Jim{\'e}nez, Mar{\'\i}a Jos{\'e} and Anti{\v n}olo, Guillermo and Dopazo, Joaquin and Borrego, Salud} } @article {405, title = {Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape.}, journal = {Cancer Res}, volume = {78}, year = {2018}, month = {2018 Nov 01}, pages = {6059-6072}, abstract = {

Metabolic reprogramming plays an important role in cancer development and progression and is a well-established hallmark of cancer. Despite its inherent complexity, cellular metabolism can be decomposed into functional modules that represent fundamental metabolic processes. Here, we performed a pan-cancer study involving 9,428 samples from 25 cancer types to reveal metabolic modules whose individual or coordinated activity predict cancer type and outcome, in turn highlighting novel therapeutic opportunities. Integration of gene expression levels into metabolic modules suggests that the activity of specific modules differs between cancers and the corresponding tissues of origin. Some modules may cooperate, as indicated by the positive correlation of their activity across a range of tumors. The activity of many metabolic modules was significantly associated with prognosis at a stronger magnitude than any of their constituent genes. Thus, modules may be classified as tumor suppressors and oncomodules according to their potential impact on cancer progression. Using this modeling framework, we also propose novel potential therapeutic targets that constitute alternative ways of treating cancer by inhibiting their reprogrammed metabolism. Collectively, this study provides an extensive resource of predicted cancer metabolic profiles and dependencies. Combining gene expression with metabolic modules identifies molecular mechanisms of cancer undetected on an individual gene level and allows discovery of new potential therapeutic targets. .

}, keywords = {Cell Line, Tumor, Cluster Analysis, Disease Progression, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Humans, Kaplan-Meier Estimate, Metabolome, mutation, Neoplasms, Oncogenes, Phenotype, Prognosis, RNA, Small Interfering, Sequence Analysis, RNA, Transcriptome, Treatment Outcome}, issn = {1538-7445}, doi = {10.1158/0008-5472.CAN-17-2705}, author = {Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Pujana, Miguel A and Mateo, Francesca and Herranz, Carmen and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} } @article {398, title = {Genomics of the origin and evolution of Citrus.}, journal = {Nature}, volume = {554}, year = {2018}, month = {2018 Feb 15}, pages = {311-316}, abstract = {

The genus Citrus, comprising some of the most widely cultivated fruit crops worldwide, includes an uncertain number of species. Here we describe ten natural citrus species, using genomic, phylogenetic and biogeographic analyses of 60 accessions representing diverse citrus germ plasms, and propose that citrus diversified during the late Miocene epoch through a rapid southeast Asian radiation that correlates with a marked weakening of the monsoons. A second radiation enabled by migration across the Wallace line gave rise to the Australian limes in the early Pliocene epoch. Further identification and analyses of hybrids and admixed genomes provides insights into the genealogy of major commercial cultivars of citrus. Among mandarins and sweet orange, we find an extensive network of relatedness that illuminates the domestication of these groups. Widespread pummelo admixture among these mandarins and its correlation with fruit size and acidity suggests a plausible role of pummelo introgression in the selection of palatable mandarins. This work provides a new evolutionary framework for the genus Citrus.

}, keywords = {Asia, Southeastern, Biodiversity, citrus, Crop Production, Evolution, Molecular, Genetic Speciation, Genome, Plant, Genomics, Haplotypes, Heterozygote, History, Ancient, Human Migration, Hybridization, Genetic, Phylogeny}, issn = {1476-4687}, doi = {10.1038/nature25447}, author = {Wu, Guohong Albert and Terol, Javier and Iba{\~n}ez, Victoria and L{\'o}pez-Garc{\'\i}a, Antonio and P{\'e}rez-Rom{\'a}n, Estela and Borred{\'a}, Carles and Domingo, Concha and Tadeo, Francisco R and Carbonell-Caballero, Jos{\'e} and Alonso, Roberto and Curk, Franck and Du, Dongliang and Ollitrault, Patrick and Roose, Mikeal L and Dopazo, Joaquin and Gmitter, Frederick G and Rokhsar, Daniel S and Talon, Manuel} } @article {384, title = {Genomic expression differences between cutaneous cells from red hair color individuals and black hair color individuals based on bioinformatic analysis.}, journal = {Oncotarget}, volume = {8}, year = {2017}, month = {2017 Feb 14}, pages = {11589-11599}, abstract = {

The MC1R gene plays a crucial role in pigmentation synthesis. Loss-of-function MC1R variants, which impair protein function, are associated with red hair color (RHC) phenotype and increased skin cancer risk. Cultured cutaneous cells bearing loss-of-function MC1R variants show a distinct gene expression profile compared to wild-type MC1R cultured cutaneous cells. We analysed the gene signature associated with RHC co-cultured melanocytes and keratinocytes by Protein-Protein interaction (PPI) network analysis to identify genes related with non-functional MC1R variants. From two detected networks, we selected 23 nodes as hub genes based on topological parameters. Differential expression of hub genes was then evaluated in healthy skin biopsies from RHC and black hair color (BHC) individuals. We also compared gene expression in melanoma tumors from individuals with RHC versus BHC. Gene expression in normal skin from RHC cutaneous cells showed dysregulation in 8 out of 23 hub genes (CLN3, ATG10, WIPI2, SNX2, GABARAPL2, YWHA, PCNA and GBAS). Hub genes did not differ between melanoma tumors in RHC versus BHC individuals. The study suggests that healthy skin cells from RHC individuals present a constitutive genomic deregulation associated with the red hair phenotype and identify novel genes involved in melanocyte biology.

}, keywords = {Adult, Coculture Techniques, Computational Biology, gene expression, Genetic Predisposition to Disease, Genomics, Hair Color, Humans, Keratinocytes, Melanocytes, Middle Aged, Phenotype, Receptor, Melanocortin, Type 1}, issn = {1949-2553}, doi = {10.18632/oncotarget.14140}, url = {http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget\&page=article\&op=view\&path\%5B\%5D=14140\&path\%5B\%5D=45094}, author = {Puig-Butille, Joan Anton and Gimenez-Xavier, Pol and Visconti, Alessia and Nsengimana, J{\'e}r{\'e}mie and Garcia-Garcia, Francisco and Tell-Marti, Gemma and Escamez, Maria Jos{\'e} and Newton-Bishop, Julia and Bataille, Veronique and Del Rio, Marcela and Dopazo, Joaquin and Falchi, Mario and Puig, Susana} } @article {386, title = {GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.}, journal = {N Engl J Med}, volume = {376}, year = {2017}, month = {2017 May 04}, pages = {1794-1795}, keywords = {Aged, Amino Acid Sequence, Bone Density Conservation Agents, Dimethylallyltranstransferase, Diphosphonates, Exome, Farnesyltranstransferase, Female, Femoral Fractures, Geranyltranstransferase, Humans, Middle Aged, mutation}, issn = {1533-4406}, doi = {10.1056/NEJMc1612804}, url = {http://www.nejm.org/doi/full/10.1056/NEJMc1612804}, author = {Roca-Ayats, Neus and Balcells, Susana and Garcia-Giralt, Nat{\`a}lia and Falc{\'o}-Mascar{\'o}, Maite and Mart{\'\i}nez-Gil, N{\'u}ria and Abril, Josep F and Urreizti, Roser and Dopazo, Joaquin and Quesada-G{\'o}mez, Jos{\'e} M and Nogu{\'e}s, Xavier and Mellibovsky, Leonardo and Prieto-Alhambra, Daniel and Dunford, James E and Javaid, Muhammad K and Russell, R Graham and Grinberg, Daniel and D{\'\i}ez-P{\'e}rez, Adolfo} } @article {457, title = {Global Transcriptome Analysis of Primary Cerebrocortical Cells: Identification of Genes Regulated by Triiodothyronine in Specific Cell Types.}, journal = {Cereb Cortex}, volume = {27}, year = {2017}, month = {2017 01 01}, pages = {706-717}, abstract = {

Thyroid hormones, thyroxine, and triiodothyronine (T3) are crucial for cerebral cortex development acting through regulation of gene expression. To define the transcriptional program under T3 regulation, we have performed RNA-Seq of T3-treated and untreated primary mouse cerebrocortical cells. The expression of 1145 genes or 7.7\% of expressed genes was changed upon T3 addition, of which 371 responded to T3 in the presence of cycloheximide indicating direct transcriptional regulation. The results were compared with available transcriptomic datasets of defined cellular types. In this way, we could identify targets of T3 within genes enriched in astrocytes and neurons, in specific layers including the subplate, and in specific neurons such as prepronociceptin, cholecystokinin, or cortistatin neurons. The subplate and the prepronociceptin neurons appear as potentially major targets of T3 action. T3 upregulates mostly genes related to cell membrane events, such as G-protein signaling, neurotransmission, and ion transport and downregulates genes involved in nuclear events associated with the M phase of cell cycle, such as chromosome organization and segregation. Remarkably, the transcriptomic changes induced by T3 sustain the transition from fetal to adult patterns of gene expression. The results allow defining in molecular terms the elusive role of thyroid hormones on neocortical development.

}, keywords = {Animals, Astrocytes, Cells, Cultured, Cerebral Cortex, Fluorescent Antibody Technique, Gene Expression Profiling, Mice, 129 Strain, Mice, Inbred BALB C, Mice, Inbred C57BL, Neurons, Piperazines, Transcriptome, Triiodothyronine}, issn = {1460-2199}, doi = {10.1093/cercor/bhv273}, author = {Gil-Iba{\~n}ez, Pilar and Garcia-Garcia, Francisco and Dopazo, Joaquin and Bernal, Juan and Morte, Beatriz} } @article {399, title = {Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes.}, journal = {BMC Syst Biol}, volume = {11}, year = {2017}, month = {2017 Nov 22}, pages = {110}, abstract = {

BACKGROUND: Identification of driver genes related to certain types of cancer is an important research topic. Several systems biology approaches have been suggested, in particular for the identification of breast cancer (BRCA) related genes. Such approaches usually rely on differential gene expression and/or mutational landscape data. In some cases interaction network data is also integrated to identify cancer-related modules computationally.

RESULTS: We provide a framework for the comparative graph-theoretical analysis of networks integrating the relevant gene expression, mutations, and potein-protein interaction network data. The comparisons involve a graph-theoretical analysis of normal and tumor network pairs across all instances of a given set of breast cancer samples. The network measures under consideration are based on appropriate formulations of various centrality measures: betweenness, clustering coefficients, degree centrality, random walk distances, graph-theoretical distances, and Jaccard index centrality.

CONCLUSIONS: Among all the studied centrality-based graph-theoretical properties, we show that a betweenness-based measure differentiates BRCA genes across all normal versus tumor network pairs, than the rest of the popular centrality-based measures. The AUROC and AUPR values of the gene lists ordered with respect to the measures under study as compared to NCBI BioSystems pathway and the COSMIC database of cancer genes are the largest with the betweenness-based differentiation, followed by the measure based on degree centrality. In order to test the robustness of the suggested measures in prioritizing cancer genes, we further tested the two most promising measures, those based on betweenness and degree centralities, on randomly rewired networks. We show that both measures are quite resilient to noise in the input interaction network. We also compared the same measures against a state-of-the-art alternative disease gene prioritization method, MUFFFINN. We show that both our graph-theoretical measures outperform MUFFINN prioritizations in terms of ROC and precions/recall analysis. Finally, we filter the ordered list of the best measure, the betweenness-based differentiation, via a maximum-weight independent set formulation and investigate the top 50 genes in regards to literature verification. We show that almost all genes in the list are verified by the breast cancer literature and three genes are presented as novel genes that may potentialy be BRCA-related but missing in literature.

}, keywords = {Breast Neoplasms, Female, Gene Regulatory Networks, Genes, Tumor Suppressor, Humans, Models, Theoretical, mutation}, issn = {1752-0509}, doi = {10.1186/s12918-017-0495-0}, author = {Dopazo, Joaquin and Erten, Cesim} } @article {429, title = {Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes}, journal = {BMC Systems Biology}, volume = {11}, year = {2017}, month = {Jan-12-2017}, doi = {10.1186/s12918-017-0495-0}, url = {https://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-017-0495-0http://link.springer.com/content/pdf/10.1186/s12918-017-0495-0.pdf}, author = {Dopazo, Joaquin and Erten, Cesim} } @article {1005, title = {Genomics and transcriptomics in drug discovery.}, journal = {Drug discovery today}, volume = {19}, number = {2}, year = {2014}, month = {2013 Jun 14}, pages = {126-32}, abstract = {The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.}, keywords = {adverse effects, Drug discovery, drug repositioning, metagenomics, modeling, network analysis, pathway analysis}, issn = {1878-5832}, doi = {10.1016/j.drudis.2013.06.003}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23773860}, author = {Dopazo, Joaquin} } @article {1003, title = {Genome Maps, a new generation genome browser.}, journal = {Nucleic acids research}, volume = {41}, number = {W1}, year = {2013}, month = {2013 Jun 8}, pages = {W41-W46}, abstract = {Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.}, keywords = {BAM, genome viewer, HTML5, javascript, Next Generation Sequencing, NGS, SVG, VCF}, issn = {1362-4962}, doi = {10.1093/nar/gkt530}, url = {http://nar.oxfordjournals.org/content/41/W1/W41}, author = {Medina, Ignacio and Salavert, Francisco and S{\'a}nchez, Rub{\'e}n and De Maria, Alejandro and Alonso, Roberto and Escobar, Pablo and Bleda, Marta and Joaqu{\'\i}n Dopazo} } @article {957, title = {Grape antioxidant dietary fiber (GADF) inhibits intestinal polyposis in ApcMin/+ mice: relation to cell cycle and immune response.}, journal = {Carcinogenesis}, year = {2013}, month = {2013 Apr 24}, abstract = {Epidemiological and experimental studies suggest that fiber and phenolic compounds might have a protective effect on the development of colon cancer in humans. Accordingly, we assessed the chemopreventive efficacy and associated mechanisms of action of a lyophilized red grape pomace containing proanthocyanidin-rich dietary fiber (Grape Antioxidant Dietary Fiber, GADF) on spontaneous intestinal tumorigenesis in the Apc(Min/+) mouse model. Mice were fed a standard diet (control group) or a 1\% (w/w) GADF-supplemented diet (GADF group) for 6 weeks. GADF supplementation greatly reduced intestinal tumorigenesis, significantly decreasing the total number of polyps by 76\%. Moreover, size distribution analysis showed a considerable reduction in all polyp size categories [diameter <1 mm (65\%), 1-2 mm (67\%) and >2 mm (87\%)]. In terms of polyp formation in the proximal, middle and distal portions of the small intestine a decrease of 76\%, 81\% and 73\% was observed respectively. Putative molecular mechanisms underlying the inhibition of intestinal tumorigenesis were investigated by comparison of microarray expression profiles of GADF-treated and non-treated mice. We observed that the effects of GADF are mainly associated with the induction of a G1 cell cycle arrest and the downregulation of genes related to the immune response and inflammation. Our findings show for the first time the efficacy and associated mechanisms of action of GADF against intestinal tumorigenesis in Apc(Min/+) mice, suggesting its potential for the prevention of colorectal cancer.}, issn = {1460-2180}, doi = {10.1093/carcin/bgt140}, url = {http://carcin.oxfordjournals.org/content/early/2013/04/23/carcin.bgt140.abstract}, author = {S{\'a}nchez-Tena, Susana and Lizarraga, Daneida and Miranda, Anibal and Vinardell, Maria Pilar and Garcia-Garcia, Francisco and Joaqu{\'\i}n Dopazo and Torres, Josep Llu{\'\i}s and Saura-Calixto, Fulgencio and Capell{\`a}, Gabriel and Cascante, Marta} } @article {497, title = {Grape antioxidant dietary fiber inhibits intestinal polyposis in ApcMin/+ mice: relation to cell cycle and immune response.}, journal = {Carcinogenesis}, volume = {34}, year = {2013}, month = {2013 Aug}, pages = {1881-8}, abstract = {

Epidemiological and experimental studies suggest that fiber and phenolic compounds might have a protective effect on the development of colon cancer in humans. Accordingly, we assessed the chemopreventive efficacy and associated mechanisms of action of a lyophilized red grape pomace containing proanthocyanidin (PA)-rich dietary fiber [grape antioxidant dietary fiber (GADF)] on spontaneous intestinal tumorigenesis in the Apc(Min/+) mouse model. Mice were fed a standard diet (control group) or a 1\% (w/w) GADF-supplemented diet (GADF group) for 6 weeks. GADF supplementation greatly reduced intestinal tumorigenesis, significantly decreasing the total number of polyps by 76\%. Moreover, size distribution analysis showed a considerable reduction in all polyp size categories [diameter <1mm (65\%), 1-2mm (67\%) and >2mm (87\%)]. In terms of polyp formation in the proximal, middle and distal portions of the small intestine, a decrease of 76, 81 and 73\% was observed, respectively. Putative molecular mechanisms underlying the inhibition of intestinal tumorigenesis were investigated by comparison of microarray expression profiles of GADF-treated and non-treated mice. We observed that the effects of GADF are mainly associated with the induction of a G1 cell cycle arrest and the downregulation of genes related to the immune response and inflammation. Our findings show for the first time the efficacy and associated mechanisms of action of GADF against intestinal tumorigenesis in Apc(Min/+) mice, suggesting its potential for the prevention of colorectal cancer.

}, keywords = {Animals, Antioxidants, Body Weight, Carcinogenesis, Cell Cycle, Cell Cycle Checkpoints, Colorectal Neoplasms, Dietary Fiber, Dietary Supplements, Down-Regulation, G1 Phase, Inflammation, Intestinal Polyposis, Intestinal Polyps, Intestine, Small, Male, Mice, Transcriptome, Vitis}, issn = {1460-2180}, doi = {10.1093/carcin/bgt140}, author = {S{\'a}nchez-Tena, Susana and Lizarraga, Daneida and Miranda, Anibal and Vinardell, Maria P and Garcia-Garcia, Francisco and Dopazo, Joaquin and Torres, Josep L and Saura-Calixto, Fulgencio and Capell{\`a}, Gabriel and Cascante, Marta} } @article {21824869, title = {Genome-wide heterogeneity of nucleotide substitution model fit.}, journal = {Genome biology and evolution}, volume = {3}, year = {2011}, month = {2011}, pages = {896-908}, abstract = {

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95\% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

}, author = {Arbiza, Leonardo and Patricio, Mateus and Dopazo, Hern{\'a}n and Posada, David} } @article {582, title = {Gene set internal coherence in the context of functional profiling.}, journal = {BMC Genomics}, volume = {10}, year = {2009}, month = {2009 Apr 27}, pages = {197}, abstract = {

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}, issn = {1471-2164}, doi = {10.1186/1471-2164-10-197}, author = {Montaner, David and Minguez, Pablo and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @article {583, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.}, journal = {Nucleic Acids Res}, volume = {37}, year = {2009}, month = {2009 Jul}, pages = {W340-4}, abstract = {

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}, issn = {1362-4962}, doi = {10.1093/nar/gkp481}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @article {IgnacioMedina07012009, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies}, journal = {Nucl. Acids Res.}, volume = {37}, number = {suppl_2}, year = {2009}, pages = {W340-344}, abstract = {

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 = {babelomics, gene set, GESBAP, pathway-based analysis, SNP}, doi = {10.1093/nar/gkp481}, url = {http://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W340}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Fatima Al-Shahrour and Dopazo, Joaquin} } @inbook {761, title = {Gen{\'o}mica Comparativa y Selecci{\'o}n Natural. Aplicaciones en el Genoma Humano. Cap{\'\i}tulo 1.6}, booktitle = {Evoluci{\'o}n y Adaptac{\'o}n. 150 a{\~n}os despu{\'e}s del Origen de las Especies}, year = {2009}, pages = {51-59}, publisher = {Obrapropia.}, organization = {Obrapropia.}, chapter = {19}, address = {Valencia}, abstract = {

La b\úsqueda de los eventos adaptativos a nivel molecular que ha diferenciado el genoma humano del de nuestro pariente vivo m\ás cercano, el chimpanc\é, ha sido una de las \áreas de mayor investigaci\ón en gen\ómica comparativa. Paralelamente, la predicci\ón funcional de variantes gen\éticas en nuestra especie ha sido un \área de intenso desarrollo en bioinform\ática. En este trabajo discutiremos resultados previos y otros m\ás recientes que dan cuenta de estos desarrollos. Veremos que en todos los casos la estimaci\ón de las presiones selectivas a nivel de los genes individuales o de los residuos de las prote\ínas son el denominador com\ún para discutir ambos aspectos. Finalmente mostraremos c\ómo el an\álisis de estas presiones selectivas por grupos funcionales de genes resulta una alternativa viable y con suficiente poder estad\ístico para el an\álisis de la adaptaci\ón y de las restricciones evolutivas a nivel gen\ómico.\ 

}, issn = {978-84-92910-06-9}, author = {Serra, Fran{\c c}ois and Arbiza, L. and H. Dopazo}, editor = {H. Dopazo and Navarro, A.} } @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 {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 {15892869, title = {Genome-scale evidence of the nematode-arthropod clade}, journal = {Genome Biol}, volume = {6}, number = {5}, year = {2005}, note = {Dopazo, Hernan Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Genome biology Genome Biol. 2005;6(5):R41. Epub 2005 Apr 28.}, pages = {R41}, abstract = {BACKGROUND: The issue of whether coelomates form a single clade, the Coelomata, or whether all animals that moult an exoskeleton (such as the coelomate arthropods and the pseudocoelomate nematodes) form a distinct clade, the Ecdysozoa, is the most puzzling issue in animal systematics and a major open-ended subject in evolutionary biology. Previous single-gene and genome-scale analyses designed to resolve the issue have produced contradictory results. Here we present the first genome-scale phylogenetic evidence that strongly supports the Ecdysozoa hypothesis. RESULTS: Through the most extensive phylogenetic analysis carried out to date, the complete genomes of 11 eukaryotic species have been analyzed in order to find homologous sequences derived from 18 human chromosomes. Phylogenetic analysis of datasets showing an increased adjustment to equal evolutionary rates between nematode and arthropod sequences produced a gradual change from support for Coelomata to support for Ecdysozoa. Transition between topologies occurred when fast-evolving sequences of Caenorhabditis elegans were removed. When chordate, nematode and arthropod sequences were constrained to fit equal evolutionary rates, the Ecdysozoa topology was statistically accepted whereas Coelomata was rejected. CONCLUSIONS: The reliability of a monophyletic group clustering arthropods and nematodes was unequivocally accepted in datasets where traces of the long-branch attraction effect were removed. This is the first phylogenomic evidence to strongly support the {\textquoteright}moulting clade{\textquoteright} hypothesis.}, keywords = {Animals Arthropods/*classification/genetics Caenorhabditis elegans/classification/genetics Evolution, Molecular *Genome Genomics Nematoda/*classification/genetics *Phylogeny}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15892869}, author = {H. Dopazo 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.} } @article {15382261, title = {Gene expression analysis of chromosomal regions with gain or loss of genetic material detected by comparative genomic hybridization}, journal = {Genes Chromosomes Cancer}, volume = {41}, number = {4}, year = {2004}, note = {Melendez, Barbara Diaz-Uriarte, Ramon Cuadros, Marta Martinez-Ramirez, Angel Fernandez-Piqueras, Jose Dopazo, Ana Cigudosa, Juan-Cruz Rivas, Carmen Dopazo, Joaquin Martinez-Delgado, Beatriz Benitez, Javier Research Support, Non-U.S. Gov{\textquoteright}t United States Genes, chromosomes \& cancer Genes Chromosomes Cancer. 2004 Dec;41(4):353-65.}, pages = {353-65}, abstract = {Comparative genomic hybridization (CGH) has been widely used to detect copy number alterations in cancer and to identify regions containing candidate tumor-responsible genes; however, gene expression changes have been described only in highly amplified regions (amplicons). To study the overall impact of slight copy number changes on gene expression, we analyzed 16 T-cell lymphomas by using CGH and a custom-designed cDNA microarray containing 7,657 genes and expressed sequence tags related to tumorigenesis. We evaluated mean gene expression and variability within CGH-altered regions and explored the relationship between the effects of the gene and its position within these regions. Minimally overlapping CGH candidate areas (6q25, 13q21-q22, and 19q13.1) revealed a weak relationship between altered genomic content and gene expression. However, some candidate genes showed modified expression within these regions in the majority of tumors; these candidate genes were evaluated and confirmed in another independent series of 23 T-cell lymphomas by use of the same cDNA microarray and by FISH on a tissue microarray. When all the CGH regions detected for each tumor were considered, we found a significant increase or decrease in the mean expression of the genes contained in gained or lost regions, respectively. In addition, we found that the expression of a gene was dependent not only on its position within an altered region but also on its own mechanism of regulation: genes in the same altered region responded very differently to the gain or loss of genetic material. Supplementary material for this article can be found on the Genes, Chromosomes, and Cancer website at http://www.interscience.wiley.com/jpages/1045-2257/suppmat/index.html.}, keywords = {Chromosomes, Fluorescence Lymphoma, Human, Pair 13/*genetics Chromosomes, Pair 19/*genetics Chromosomes, Pair 6/*genetics Expressed Sequence Tags *Gene Dosage Gene Expression Profiling Humans In Situ Hybridization, T-Cell/*genetics Nucleic Acid Hybridization Oligonucleotide Array Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=15382261}, author = {Melendez, B. and Diaz-Uriarte, R. and Cuadros, M. and Martinez-Ramirez, A. and Fernandez-Piqueras, J. and Dopazo, A. and Cigudosa, J. C. and Rivas, C. and Dopazo, J. and Martinez-Delgado, B. and Benitez, J.} } @inbook {490, title = {Gene expression Correlation and Gene Ontology-Based Similarity: An Assessment of Quantitative Relationship}, booktitle = {IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology}, year = {2004}, pages = {25-31}, author = {Wang, H and F. Azuaje and Bodenreider, O and Dopazo, J.} } @article {12651726, title = {Gene expression data preprocessing}, journal = {Bioinformatics}, volume = {19}, number = {5}, year = {2003}, note = {Herrero, J Diaz-Uriarte, R Dopazo, J England Bioinformatics (Oxford, England) Bioinformatics. 2003 Mar 22;19(5):655-6.}, pages = {655-6}, abstract = {We present an interactive web tool for preprocessing microarray gene expression data. It analyses the data, suggests the most appropriate transformations and proceeds with them after user agreement. The normal preprocessing steps include scale transformations, management of missing values, replicate handling, flat pattern filtering and pattern standardization and they are required before performing any pattern analysis. The processed data set can be sent to other pattern analysis tools.}, keywords = {*Database Management Systems Gene Expression Profiling/*methods Information Storage and Retrieval/methods Internet Oligonucleotide Array Sequence Analysis/*methods Sequence Alignment/*methods Sequence Analysis, DNA/*methods *Software *User-Computer Interface}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12651726}, author = {Herrero, J. and Diaz-Uriarte, R. and Dopazo, J.} } @article {12824345, title = {GEPAS: A web-based resource for microarray gene expression data analysis}, journal = {Nucleic Acids Res}, volume = {31}, number = {13}, year = {2003}, note = {

Herrero, Javier Al-Shahrour, Fatima Diaz-Uriarte, Ramon Mateos, Alvaro Vaquerizas, Juan M Santoyo, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2003 Jul 1;31(13):3461-7.

}, pages = {3461-7}, abstract = {

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).

}, keywords = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12824345}, author = {Herrero, J. and Fatima Al-Shahrour and Diaz-Uriarte, R. and A. Mateos and Vaquerizas, J. M. and J. Santoyo and Dopazo, J.} }