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Minguez P, Al-Shahrour F, Montaner D, Dopazo J. Functional profiling of microarray experiments using text-mining derived bioentities. Bioinformatics. 2007;23:3098-9. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17855415.
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.
Minguez P, Dopazo J. Protein Interactions for Functional Genomics. In: Li X-L, Ng S-K, eds. Biological Data Mining in Protein Interaction Networks. Biological Data Mining in Protein Interaction Networks. Hershey, USA: Idea Group Inc (IGI); 2009:223-238. Available at: http://books.google.es/books?id=pNyCy5GsqtkC.
Minguez P, Dopazo J. Functional genomics and networks: new approaches in the extraction of complex gene modules. Expert Rev Proteomics. 2010;7(1):55-63. doi:10.1586/epr.09.103.
Minguez P, Götz S, Montaner D, Al-Shahrour F, Dopazo J. SNOW, a web-based tool for the statistical analysis of protein-protein interaction networks. Nucleic Acids Res. 2009;37(Web Server issue):W109-14. doi:10.1093/nar/gkp402.
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.
Millán-Esteban D, Peña-Chilet M, García-Casado Z, et al. Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development. Cancers (Basel). 2021;13(20). doi:10.3390/cancers13205219.
Méndez-Vidal C, del Pozo MGonzález-, Vela-Boza A, et al. Whole-exome sequencing identifies novel compound heterozygous mutations in USH2A in Spanish patients with autosomal recessive retinitis pigmentosa. Molecular vision. 2013;19:2187-95. Available at: http://www.molvis.org/molvis/v19/2187/.
Méndez-Vidal C, Bravo-Gil N, del Pozo MGonzález-, et al. Novel RP1 mutations and a recurrent BBS1 variant explain the co-existence of two distinct retinal phenotypes in the same pedigree. BMC Genet. 2014;15:143. doi:10.1186/s12863-014-0143-2.
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.
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.
Melo F, Marti-Renom MA. Accuracy of sequence alignment and fold assessment using reduced amino acid alphabets. Proteins. 2006;63:986-95. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16506243.
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.
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.
Medina I, Salavert F, Sánchez R, et al. Genome Maps, a new generation genome browser. Nucleic acids research. 2013;41:W41-W46. doi:10.1093/nar/gkt530.
Medina I, Tárraga J, Martínez H, et al. Highly sensitive and ultrafast read mapping for RNA-seq analysis. DNA Res. 2016;23(2):93-100. doi:10.1093/dnares/dsv039.
Medina I, De Maria A, Bleda M, et al. VARIANT: Command Line, Web service and Web interface for fast and accurate functional characterization of variants found by Next-Generation Sequencing. Nucleic Acids Res. 2012;40(Web Server issue):W54-8. doi:10.1093/nar/gks572.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucleic Acids Res. 2009;37(Web Server issue):W340-4. doi:10.1093/nar/gkp481.
Medina I, Montaner D, Bonifaci N, et al. Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. Nucl. Acids Res. 2009;37:W340-344. doi:10.1093/nar/gkp481.
Medina I, Montaner D, Tarraga J, Dopazo J. Prophet, a web-based tool for class prediction using microarray data. Bioinformatics. 2007;23:390-1. Available at: http://bioinformatics.oxfordjournals.org/cgi/content/full/23/3/390?view=long&pmid=17138587.
McMahon SA, Miller JL, Lawton JA, et al. The C-type lectin fold as an evolutionary solution for massive sequence variation. Nat Struct Mol Biol. 2005;12:886-92. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16170324.
Mateos A, Herrero J, Dopazo J. Using perceptrons for supervised classification of DNA microarray samples: obtaining the optimal level of information and finding differentially expressed genes. In: ICANN 2002, LNCS 2415. ICANN 2002, LNCS 2415. J.R. Dorronsoro; 2002:577-582.
Mateos A, Herrero J, Tamames J, Dopazo J. Supervised Neural Networks For Clustering Conditions In DNA Array Data After Reducing Noise By Clustering Gene Expression Profiles. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:91-103.
Mateos A, Dopazo J, Jansen R, Tu Y, Gerstein M, Stolovitzky G. Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons. Genome Res. 2002;12:1703-15. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12421757.
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.