Méndez-Vidal C, Bravo-Gil N, Perez-Florido J, et al. A genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice. J Transl Med. 2025;23(1):86. doi:10.1186/s12967-025-06069-2.

Martínez-Nava GAngélica, Altamirano-Molina E, Vázquez-Mellado J, et al. Metatranscriptomic analysis reveals gut microbiome bacterial genes in pyruvate and amino acid metabolism associated with hyperuricemia and gout in humans. Sci Rep. 2025;15(1):9981. doi:10.1038/s41598-025-93899-1.

Greene D, De Wispelaere K, Lees J, et al. Mutations in the small nuclear RNA gene RNU2-2 cause a severe neurodevelopmental disorder with prominent epilepsy. Nature Genetics. 2025. doi:10.1038/s41588-025-02159-5.

Niarakis A, Ostaszewski M, Mazein A, et al. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front Immunol. 2024;14:1282859. doi:10.3389/fimmu.2023.1282859.

Fernández-Palacios P, Galán-Sánchez F, Casimiro-Soriguer CS, et al. Genotypic characterization and antimicrobial susceptibility of human  isolates in Southern Spain. Microbiol Spectr. 2024;12(10):e0102824. doi:10.1128/spectrum.01028-24.

Mavillard F, Perez-Florido J, Ortuno FM, et al. The Iberian Roma Population Variant Server (IRPVS). J Genet Genomics. 2024. doi:10.1016/j.jgg.2024.03.006.

Casimiro-Soriguer CS, Perez-Florido J, Lara M, et al. Molecular and phylogenetic characterization of the monkeypox outbreak in the South of Spain. Health Sci Rep. 2024;7(3):e1965. doi:10.1002/hsr2.1965.

Baz-Redón N, Sánchez-Bellver L, Fernández-Cancio M, et al. Primary Ciliary Dyskinesia and Retinitis Pigmentosa: Novel  Variant and Possible Modifier Gene. Cells. 2024;13(6). doi:10.3390/cells13060524.

López-López D, Roldán G, Fernandez-Rueda JL, et al. A crowdsourcing database for the copy-number variation of the Spanish population. Hum Genomics. 2023;17(1):20. doi:10.1186/s40246-023-00466-8.

Pellegrinelli V, Figueroa-Juárez E, Samuelson I, et al. Defective extracellular matrix remodeling in brown adipose tissue is associated with fibro-inflammation and reduced diet-induced thermogenesis. Cell Rep. 2023;42(6):112640. doi:10.1016/j.celrep.2023.112640.

Perez-Florido J, Casimiro-Soriguer CS, Ortuno F, et al. Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia. Int J Mol Sci. 2023;24(3). doi:10.3390/ijms24032419.

Chaves-Blanco L, de Salazar A, Fuentes A, et al. Evaluation of a combined detection of SARS-CoV-2 and its variants using real-time allele-specific PCR strategy: an advantage for clinical practice. Epidemiol Infect. 2023;151:e201. doi:10.1017/S095026882300184X.

Gawron P, Hoksza D, Piñero J, et al. Visualization of automatically combined disease maps and pathway diagrams for rare diseases. Front Bioinform. 2023;3:1101505. doi:10.3389/fbinf.2023.1101505.

Luque J, Mendes I, Gómez B, et al. CIBERER: Spanish National Network for Research on Rare Diseases: a highly productive collaborative initiative. Clin Genet. 2022. doi:10.1111/cge.14113.

Torrent-Vernetta A, Gaboli M, Castillo-Corullón S, et al. Incidence and Prevalence of Children's Diffuse Lung Disease in Spain. Arch Bronconeumol. 2022;58(1):22-29. doi:10.1016/j.arbres.2021.06.001.

Cruz R, de Almeida SDiz-, Heredia MLópez, et al. Novel genes and sex differences in COVID-19 severity. Hum Mol Genet. 2022. doi:10.1093/hmg/ddac132.

Ostaszewski M, Niarakis A, Mazein A, et al. COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. Mol Syst Biol. 2021;17(10):e10387. doi:10.15252/msb.202110387.

Peña-Chilet M, Roldán G, Perez-Florido J, et al. CSVS, a crowdsourcing database of the Spanish population genetic variability. Nucleic Acids Res. 2021;49(D1):D1130-D1137. doi:10.1093/nar/gkaa794.

Moura DS, Peña-Chilet M, Varela JAntonio Co, et al. A DNA damage repair gene-associated signature predicts responses of patients with advanced soft-tissue sarcoma to treatment with trabectedin. Mol Oncol. 2021;15(12):3691-3705. doi:10.1002/1878-0261.12996.

Walsh I, Fishman D, Garcia-Gasulla D, et al. DOME: recommendations for supervised machine learning validation in biology. Nat Methods. 2021;18(10):1122-1127. doi:10.1038/s41592-021-01205-4.

Rian K, Hidalgo MR, Cubuk C, et al. Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data. Computational and Structural Biotechnology Journal. 2021;19:2968 - 2978. doi:10.1016/j.csbj.2021.05.022.

Villalba-Benito L, López-López D, Torroglosa A, et al. Genome-wide analysis of DNA methylation in Hirschsprung enteric precursor cells: unraveling the epigenetic landscape of enteric nervous system developmentAbstractBackgroundResultsConclusionsGraphic abstract. Clinical Epigenetics. 2021;13(1). doi:10.1186/s13148-021-01040-6.

Rian K, Esteban-Medina M, Hidalgo MR, et al. Mechanistic modeling of the SARS-CoV-2 disease map. BioData Min. 2021;14(1):5. doi:10.1186/s13040-021-00234-1.

Heath AP, Ferretti V, Agrawal S, et al. The NCI Genomic Data Commons. Nature Genetics. 2021. doi:10.1038/s41588-021-00791-5.

Casimiro-Soriguer CS, Perez-Florido J, Fernandez-Rueda JL, et al. Phylogenetic Analysis of the 2020 West Nile Virus (WNV) Outbreak in Andalusia (Spain). Viruses. 2021;13(5):836. doi:10.3390/v13050836.

Mirzayi C, Renson A, Zohra F, et al. Reporting guidelines for human microbiome research: the STORMS checklist. Nat Med. 2021;27(11):1885-1892. doi:10.1038/s41591-021-01552-x.

Méndez-Salazar EOrlando, Vázquez-Mellado J, Casimiro-Soriguer CS, et al. Taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism. Mol Med. 2021;27(1):50. doi:10.1186/s10020-021-00311-5.

Yang M, Petralia F, Li Z, et al. Community Assessment of the Predictability of Cancer Protein and Phosphoprotein Levels from Genomics and Transcriptomics. Cell Syst. 2020;11(2):186-195.e9. doi:10.1016/j.cels.2020.06.013.

Ostaszewski M, Mazein A, Gillespie ME, et al. COVID-19 Disease Map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms. Sci Data. 2020;7(1):136. doi:10.1038/s41597-020-0477-8.

Loucera C, Esteban-Medina M, Rian K, Falco MM, Dopazo J, Peña-Chilet M. Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection. Signal Transduct Target Ther. 2020;5(1):290. doi:10.1038/s41392-020-00417-y.

Salgado D, Armean IM, Baudis M, et al. The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research. F1000Res. 2020;9. doi:10.12688/f1000research.24887.1.

Palomero L, Galván-Femenía I, de Cid R, et al. Immune Cell Associations with Cancer Risk. iScience. 2020;23(7):101296. doi:10.1016/j.isci.2020.101296.

Falco MM, Peña-Chilet M, Loucera C, Hidalgo MR, Dopazo J. Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscapeAbstract. NAR Cancer. 2020;2(2). doi:10.1093/narcan/zcaa011.

Bogliolo M, Pujol R, Aza-Carmona M, et al. Optimised molecular genetic diagnostics of Fanconi anaemia by whole exome sequencing and functional studies. J Med Genet. 2020;57(4):258-268. doi:10.1136/jmedgenet-2019-106249.

Martin-Broto J, Cruz J, Penel N, et al. Pazopanib for treatment of typical solitary fibrous tumours: a multicentre, single-arm, phase 2 trial. Lancet Oncol. 2020;21(3):456-466. doi:10.1016/S1470-2045(19)30826-5.

Bojic S, Falco MM, Stojkovic P, et al. Platform to study intracellular polystyrene nanoplastic pollution and clinical outcomes. Stem Cells. 2020;38(10):1321-1325. doi:10.1002/stem.3244.

Casimiro-Soriguer CS, Loucera C, Florido JPerez, López-López D, Dopazo J. Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples. Biol Direct. 2019;14(1):15. doi:10.1186/s13062-019-0246-9.

Menden MP, Wang D, Mason MJ, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10(1):2674. doi:10.1038/s41467-019-09799-2.

Peña-Chilet M, Esteban-Medina M, Falco MM, et al. Using mechanistic models for the clinical interpretation of complex genomic variation. Scientific Reports. 2019;9(1). doi:10.1038/s41598-019-55454-7.

Fourati S, Talla A, Mahmoudian M, et al. A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-06735-8.

Ferreira PG, Muñoz-Aguirre M, Reverter F, et al. The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat Commun. 2018;9(1):490. doi:10.1038/s41467-017-02772-x.

López M, Rueda A, Florido JP, et al. Evolution of the Quorum network and the mobilome (plasmids and bacteriophages) in clinical strains of Acinetobacter baumannii during a decade. Sci Rep. 2018;8(1):2523. doi:10.1038/s41598-018-20847-7.

Hernáez JRodríguez, Cucchi MEsperanza, Cravero S, et al. The first complete genomic structure of Butyrivibrio fibrisolvens and its chromid. Microb Genom. 2018;4(10). doi:10.1099/mgen.0.000216.

Cobo-Vuilleumier N, Lorenzo PI, Rodríguez NGarcía, et al. LRH-1 agonism favours an immune-islet dialogue which protects against diabetes mellitus. Nat Commun. 2018;9(1):1488. doi:10.1038/s41467-018-03943-0.

Gonzalez S, Clavijo B, Rivarola M, et al. ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data. BMC Bioinformatics. 2017;18(1):121. doi:10.1186/s12859-017-1494-2.

Puig-Butille JAnton, Gimenez-Xavier P, Visconti A, et al. Genomic expression differences between cutaneous cells from red hair color individuals and black hair color individuals based on bioinformatic analysis. Oncotarget. 2017;8(7):11589-11599. doi:10.18632/oncotarget.14140.

Roca-Ayats N, Balcells S, Garcia-Giralt N, et al. GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates. N Engl J Med. 2017;376(18):1794-1795. doi:10.1056/NEJMc1612804.

Lopez J, Coll J, Haimel M, et al. HGVA: the Human Genome Variation Archive. Nucleic Acids Res. 2017;45(W1):W189-W194. doi:10.1093/nar/gkx445.

Moschen S, Di Rienzo JA, Higgins J, et al. Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.). Plant Mol Biol. 2017;94(4-5):549-564. doi:10.1007/s11103-017-0625-5.

Matalonga L, Bravo M, Serra-Peinado C, et al. Mutations in TRAPPC11 are associated with a congenital disorder of glycosylation. Hum Mutat. 2017;38(2):148-151. doi:10.1002/humu.23145.

Dopazo J, Amadoz A, Bleda M, et al. 267 Spanish exomes reveal population-specific differences in disease-related genetic variation. Molecular biology and evolution. 2016. doi:10.1093/molbev/msw005.

Sanchez-Mut JV, Heyn H, Vidal E, et al. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry. 2016;6:e718. doi:10.1038/tp.2015.214.

Corton M, Avila-Fernández A, Campello L, et al. Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa. Sci Rep. 2016;6:35370. doi:10.1038/srep35370.

Moschen S, Luoni SBengoa, Di Rienzo JA, et al. Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower. Plant Biotechnol J. 2016;14(2):719-34. doi:10.1111/pbi.12422.

Falco MM, Bleda M, Carbonell-Caballero J, Dopazo J. The pan-cancer pathological regulatory landscape. Scientific reports. 2016;6:39709. doi:10.1038/srep39709.

Falco MM, Bleda M, Carbonell-Caballero J, Dopazo J. The pan-cancer pathological regulatory landscape. Scientific Reports. 2016;6(1). doi:10.1038/srep39709.

Razzoli M, Frontini A, Gurney A, et al. Stress-induced activation of brown adipose tissue prevents obesity in conditions of low adaptive thermogenesis. Mol Metab. 2016;5(1):19-33. doi:10.1016/j.molmet.2015.10.005.

Ewing AD, Houlahan KE, Hu Y, et al. Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. participants ICGC-TCGADREAMSoma, Xi L, Dewal N, et al., eds. Nature methods. 2015. doi:10.1038/nmeth.3407.

de la Rosa LRodríguez, Sánchez-Calderón H, Contreras J, et al. Comparative gene expression study of the vestibular organ of the Igf1 deficient mouse using whole-transcript arrays. Hearing research. 2015. doi:10.1016/j.heares.2015.08.016.

Luzón-Toro B, Gui H, Ruiz-Ferrer M, et al. Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease. Scientific reports. 2015;5:16473. doi:10.1038/srep16473.

Luzón-Toro B, Gui H, Ruiz-Ferrer M, et al. Exome sequencing reveals a high genetic heterogeneity on familial Hirschsprung disease. Scientific Reports. 2015;5(1). doi:10.1038/srep16473.

Fonseca RF, de Carvalho FM, Poletta FA, et al. Family-based genome-wide association study in Patagonia confirms the association of the DMD locus and cleft lip and palate. Eur J Oral Sci. 2015;123(5):381-384. doi:10.1111/eos.12212.

Luzón-Toro B, Bleda M, Navarro E, et al. Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas. BMC medical genomics. 2015;8:83. doi:10.1186/s12920-015-0160-7.

Luzón-Toro B, Bleda M, Navarro E, et al. Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas. BMC Medical Genomics. 2015;8:83. doi:10.1186/s12920-015-0160-7.

Calzada D, Aguerri M, Baos S, et al. Therapeutic targets for olive pollen allergy defined by gene markers modulated by Ole e 1-derived peptides. Molecular immunology. 2015;64:252-61. doi:10.1016/j.molimm.2014.12.002.

Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole Exome Sequencing Reveals ZNF408 as a New Gene Associated With Autosomal Recessive Retinitis Pigmentosa with Vitreal Alterations. Human molecular genetics. 2015;24:4037-4048. doi:10.1093/hmg/ddv140.

Avila-Fernandez A, Perez-Carro R, Corton M, et al. Whole-exome sequencing reveals ZNF408 as a new gene associated with autosomal recessive retinitis pigmentosa with vitreal alterations. Hum Mol Genet. 2015;24(14):4037-48. doi:10.1093/hmg/ddv140.

Munro SA, Lund SP, P Pine S, et al. Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures. Nature communications. 2014;5:5125. doi:10.1038/ncomms6125.

F Carmona J, Davalos V, Vidal E, et al. A Comprehensive DNA Methylation Profile of Epithelial-to-Mesenchymal Transition. Cancer research. 2014;74:5608?19. doi:10.1158/0008-5472.CAN-13-3659.

Tenorio J, Mansilla A, Valencia M, et al. A New Overgrowth Syndrome is Due to Mutations in RNF125. Human mutation. 2014;35:1436?1441. doi:10.1002/humu.22689.

López-Domingo FJ, Florido JP, Rueda A, Dopazo J, Santoyo-López J. ngsCAT: a tool to assess the efficiency of targeted enrichment sequencing. Bioinformatics. 2014;30(12):1767-8. doi:10.1093/bioinformatics/btu108.

García-Cazorla A, Oyarzabal A, Fort J, et al. Two novel mutations in the BCKDK (branched-chain keto-acid dehydrogenase kinase) gene are responsible for a neurobehavioral deficit in two pediatric unrelated patients. Hum Mutat. 2014;35(4):470-7. doi:10.1002/humu.22513.

García-Cazorla A, Oyarzabal A, Fort J, et al. Two Novel Mutations in the BCKDK Gene (Branched-Chain Keto-Acid Dehydrogenase Kinase) are Responsible of a Neurobehavioral Deficit in two Pediatric Unrelated Patients. Human mutation. 2014;35:470-7. doi:10.1002/humu.22513.

Puig-Butille JAnton, Escamez MJosé, Garcia-Garcia F, et al. Capturing the biological impact of CDKN2A and MC1R genes as an early predisposing event in melanoma and non melanoma skin cancer. Oncotarget. 2013. Available at: http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=1444&path%5B%5D=1824.

Aguerri M, Calzada D, Montaner D, et al. Differential gene-expression analysis defines a molecular pattern related to olive pollen allergy. J Biol Regul Homeost Agents. 2013;27(2):337-50.

Tort F, García-Silva MTeresa, Ferrer-Cortès X, et al. Exome sequencing identifies a new mutation in SERAC1 in a patient with 3-methylglutaconic aciduria. Mol Genet Metab. 2013;110(1-2):73-7. doi:10.1016/j.ymgme.2013.04.021.

Fernández RM, Bleda M, Luzón-Toro B, et al. Pathways systematically associated to Hirschsprung?s disease. Orphanet journal of rare diseases. 2013;8:187. doi:10.1186/1750-1172-8-187.

Fernández RM, Bleda M, Luzón-Toro B, et al. Pathways systematically associated to Hirschsprung's disease. Orphanet J Rare Dis. 2013;8:187. doi:10.1186/1750-1172-8-187.

Fernandez P, Soria M, Blesa D, et al. Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray. PloS one. 2012;7:e45899. doi:10.1371/journal.pone.0045899.

Sundaram AYM, Kiron V, Dopazo J, Fernandes JMO. Diversification of the expanded teleost-specific toll-like receptor family in Atlantic cod, Gadus morhua. BMC Evol Biol. 2012;12:256. doi:10.1186/1471-2148-12-256.

Fernández RMa, Bleda M, Núñez-Torres R, et al. Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease. Orphanet J Rare Dis. 2012;7:103. doi:10.1186/1750-1172-7-103.

Fernández RMa, Bleda M, Núñez-Torres R, et al. Four new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung?s disease. Orphanet journal of rare diseases. 2012;7:103. doi:10.1186/1750-1172-7-103.

Oppert B, Dowd SE, Bouffard P, et al. Transcriptome profiling of the intoxication response of Tenebrio molitor larvae to Bacillus thuringiensis Cry3Aa protoxin. PloS one. 2012;7:e34624. doi:10.1371/journal.pone.0034624.

Trevino V, Tadesse MG, Vannucci M, et al. Analysis of normal-tumour tissue interaction in tumours: prediction of prostate cancer features from the molecular profile of adjacent normal cells. PloS one. 2011;6:e16492.

Nueda MJ, Ferrer A, Conesa A. ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Biostatistics (Oxford, England). 2011.

Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A. Differential expression in RNA-seq: a matter of depth. Genome Res. 2011;21(12):2213-23. doi:10.1101/gr.124321.111.

Prieur X, Mok CYL, Velagapudi VR, et al. Differential Lipid Partitioning Between Adipocytes and Tissue Macrophages Modulates Macrophage Lipotoxicity and M2/M1 Polarization in Obese Mice. Diabetes. 2011;60:797-809.

Gonçalves LG, Borges N, Serra F, Fernandes PL, Dopazo H, Santos H. Evolution of the biosynthesis of di-myo-inositol phosphate, a marker of adaptation to hot marine environments. Environmental microbiology. 2011. doi:10.1111/j.1462-2920.2011.02621.x.

Durban J, Juárez P, Angulo Y, et al. Profiling the venom gland transcriptomes of Costa Rican snakes by 454 pyrosequencing. BMC genomics. 2011;12:259.

Marigorta UM, Lao O, Casals F, et al. Recent human evolution has shaped geographical differences in susceptibility to disease. BMC genomics. 2011;12:55.

Javierre BM, Fernandez AF, Richter J, et al. Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome research. 2010;20:170-9.

Bediaga NG, Acha-Sagredo A, Guerra I, et al. DNA methylation epigenotypes in breast cancer molecular subtypes. Breast Cancer Res. 2010;12(5):R77. doi:10.1186/bcr2721.

Moreno-Manzano V, Rodríguez-Jiménez FJ, Aceña-Bonilla JL, et al. FM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status. The Journal of biological chemistry. 2010;285:1333-42.

Shi W, Bessarabova M, Dosymbekov D, et al. Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes. Pharmacogenomics J. 2010;10(4):310-23. doi:10.1038/tpj.2010.35.

Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature biotechnology. 2010;28:827-38. Available at: http://www.nature.com/nbt/journal/v28/n8/full/nbt.1665.html.

E. Lewintre J, C. Martin R, Montaner D, et al. Analysis of chronic lymphotic leukemia transcriptomic profile: differences between molecular subgroups. Leuk Lymphoma. 2009;50:68-79. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19127482.

Nueda MJosé, Sebastián P, Tarazona S, et al. Functional assessment of time course microarray data. BMC Bioinformatics. 2009;10 Suppl 6:S9. doi:10.1186/1471-2105-10-S6-S9.

Fornes O, Aragues R, Espadaler J, Marti-Renom MA, Sali A, Oliva B. ModLink+: Improving fold recognition by using protein-protein interactions. Bioinformatics. 2009. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19357100.

Birmingham A, Selfors LM, Forster T, et al. Statistical methods for analysis of high-throughput RNA interference screens. Nature Methods. 2009;6:569 - 575. Available at: http://dx.doi.org/10.1038/nmeth.1351.

Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0--it's better than sharing your toothbrush!. Brief Bioinform. 2008;9(3):220-31. doi:10.1093/bib/bbn003.

Wilkinson MD, Senger M, Kawas E, et al. Interoperability with Moby 1.0?it?s better than sharing your toothbrush!. Brief Bioinform. 2008;9:220-31. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18238804.

Saar K, Beck A, Bihoreau M-T, et al. SNP and haplotype mapping for genetic analysis in the rat. Nat Genet. 2008;40(5):560-6. doi:10.1038/ng.124.

Saar K, Beck A, Bihoreau MT, et al. SNP and haplotype mapping for genetic analysis in the rat. Nat Genet. 2008;40:560-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18443594.

Nueda MJ, Conesa A, Westerhuis JA, et al. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA. Bioinformatics. 2007;23:1792-800. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17519250.

Conesa A, Forment J, Gadea J, van Dijk J. Microarray Technology in Agricultural Research. In:  Microarray Technology Through Applications. Microarray Technology Through Applications. F. Falciani. Publisher: Taylor and Francis Group; 2007:173-209.

Schluter A, Fourcade S, Domenech-Estevez E, et al. PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease. Nucleic Acids Res. 2007;35:D815-22. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17135190.

Stanley WA, Fodor K, Marti-Renom MA, Schliebs W, Wilmanns M. Protein translocation into peroxisomes by ring-shaped import receptors. FEBS Lett. 2007;581:4795-802. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17884042.

Gandia M, Conesa A, Ancillo G, et al. Transcriptional response of Citrus aurantifolia to infection by Citrus tristeza virus. Virology. 2007;367:298-306. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17617431.

Milne RL, Ribas G, Gonzalez-Neira A, et al. ERCC4 associated with breast cancer risk: a two-stage case-control study using high-throughput genotyping. Cancer Res. 2006;66:9420-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17018596.

Conesa A, Nueda MJ, Ferrer A, Talon M. maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics. 2006;22:1096-102. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16481333.

Boxma B, de Graaf RM, van der Staay GW, et al. An anaerobic mitochondrion that produces hydrogen. Nature. 2005;434:74-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15744302.

Forment J, Gadea J, Huerta L, et al. Development of a citrus genome-wide EST collection and cDNA microarray as resources for genomic studies. Plant Mol Biol. 2005;57:375-91. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15830128.

Conde L, Vaquerizas JM, Ferrer-Costa C, de la Cruz X, Orozco M, Dopazo J. PupasView: a visual tool for selecting suitable SNPs, with putative pathological effect in genes, for genotyping purposes. Nucleic Acids Res. 2005;33:W501-5. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15980522.

Melendez B, Diaz-Uriarte R, Cuadros M, et al. Gene expression analysis of chromosomal regions with gain or loss of genetic material detected by comparative genomic hybridization. Genes Chromosomes Cancer. 2004;41:353-65. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15382261.

Pieper U, Eswar N, Braberg H, et al. MODBASE, a database of annotated comparative protein structure models, and associated resources. Nucleic Acids Res. 2004;32:D217-22. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=14681398.

Eswar N, John B, Mirkovic N, et al. Tools for comparative protein structure modeling and analysis. Nucleic Acids Res. 2003;31:3375-80. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824331.

Tamames J, Clark D, Herrero J, et al. Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction. J Biotechnol. 2002;98:269-83. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12141992.

Tracey L, Villuendas R, Ortiz P, et al. Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma. Am J Pathol. 2002;161:1825-37. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12414529.

Marti-Renom MA, Madhusudhan MS, Fiser A, Rost B, Sali A. Reliability of assessment of protein structure prediction methods. Structure. 2002;10:435-40. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12005441.

Dopazo J, Mendoza A, Herrero J, et al. Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate. Microb Drug Resist. 2001;7:99-125. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11442348.

Eyrich VA, Marti-Renom MA, Przybylski D, et al. EVA: continuous automatic evaluation of protein structure prediction servers. Bioinformatics. 2001;17:1242-3. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11751240.

Dopazo J, Zanders E, Dragoni I, Amphlett G, Falciani F. Methods and approaches in the analysis of gene expression data. J Immunol Methods. 2001;250:93-112. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11251224.

Elena SF, Dopazo J, de la Pena M, Flores R, Diener TO, Moya A. Phylogenetic analysis of viroid and viroid-like satellite RNAs from plants: a reassessment. J Mol Evol. 2001;53:155-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11479686.