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Author Title [ Type(Desc)] Year
Journal Article
Herrero J, Diaz-Uriarte R, Dopazo J. An approach to inferring transcriptional regulation among genes from large-scale expression data. Comp Funct Genomics. 2003;4:148-54. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18629097.
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.
Ariño J, Casamayor A, Pérez JPerez, et al. Assessing Differential Expression Measurements by Highly Parallel Pyrosequencing and DNA Microarrays: A Comparative Study. Omics : a journal of integrative biology. 2013. doi:10.1089/omi.2011.0065.
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.
Minguez P, Dopazo J. Assessing the biological significance of gene expression signatures and co-expression modules by studying their network properties. PloS one. 2011;6:e17474. doi:doi:10.1371/journal.pone.0017474.
Hernansaiz-Ballesteros RD, Salavert F, Sebastián-Leon P, Alemán A, Medina I, Dopazo J. Assessing the impact of mutations found in next generation sequencing data over human signaling pathways. Nucleic acids research. 2015;43:W270-W275. doi:10.1093/nar/gkv349.
Loucera C, Perez-Florido J, Casimiro-Soriguer CS, et al. Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival. Viruses. 2022;14(9). doi:10.3390/v14091893.
Lupo V, Garcia-Garcia F, Sancho P, et al. Assessment of Targeted Next-Generation Sequencing as a Tool for the Diagnosis of Charcot-Marie-Tooth Disease and Hereditary Motor Neuropathy. The Journal of molecular diagnostics : JMD. 2016. doi:10.1016/j.jmoldx.2015.10.005.
Díez-Fuertes F, De La Torre-Tarazona HE, Calonge E, et al. Association of a single nucleotide polymorphism in the ubxn6 gene with long-term non-progression phenotype in HIV-positive individuals. Clin Microbiol Infect. 2020;26(1):107-114. doi:10.1016/j.cmi.2019.05.015.
Ruiz-Llorente S, Montero-Conde C, Milne RL, et al. Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma. Cancer Res. 2007;67:9561-7. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17909067.
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.
Götz S, Arnold R, Sebastián-Leon P, et al. B2G-FAR, a species centered GO annotation repository. Bioinformatics (Oxford, England). 2011;27:919-924.
Alonso R, Salavert F, Garcia-Garcia F, et al. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucleic acids research. 2015;43:W117-W121. doi:10.1093/nar/gkv384.
Al-Shahrour F, Minguez P, Vaquerizas JM, Conde L, Dopazo J. BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Res. 2005;33:W460-4. Available at: http://nar.oxfordjournals.org/content/33/suppl_2/W460.long.
Al-Shahrour F, Minguez P, Tarraga J, et al. BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Res. 2006;34:W472-6. Available at: http://nar.oxfordjournals.org/content/34/suppl_2/W472.long.
Al-Shahrour F, Carbonell J, Minguez P, et al. Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments. Nucleic Acids Res. 2008;36:W341-6. Available at: http://nar.oxfordjournals.org/content/36/suppl_2/W341.long.
Medina I, Carbonell J, Pulido L, et al. Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Nucleic Acids Research. 2010;38:W210-W213. Featured in NAR. Available at: http://nar.oxfordjournals.org/content/38/suppl_2/W210.full.
Dopazo H. Bioinformática, Genómica y Evolución. Una alianza estratégica para la biología de este siglo. Ciencia Hoy. 2009;19:88-93.
Dopazo J. Bioinformatics and cancer: an essential alliance. Clin Transl Oncol. 2006;8:409-15. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16790393.
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.
Bonifaci N, Berenguer A, Diez J, et al. Biological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes. BMC Med Genomics. 2008;1:62. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19094230.
Conesa A, Gotz S. Blast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics. Int J Plant Genomics. 2008;2008:619832. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18483572.
Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21:3674-6. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16081474.
Aparicio G, Gotz S, Conesa A, et al. Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis. Stud Health Technol Inform. 2006;120:194-204. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16823138.
Romero A, Garcia-Garcia F, López-Perolio I, et al. BRCA1 Alternative splicing landscape in breast tissue samples. BMC cancer. 2015;15:219. doi:10.1186/s12885-015-1145-9.