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D
Dopazo J, Erten C. Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes. BMC Syst Biol. 2017;11(1):110. doi:10.1186/s12918-017-0495-0.
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.
Dopazo H, Dopazo J. Genome-scale evidence of the nematode-arthropod clade. Genome Biol. 2005;6:R41. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15892869.
Dopazo H, Gordon MB, Perazzo R, Risau-Gusman S. A model for the emergence of adaptive subsystems. Bull Math Biol. 2003;65:27-56. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12597115.
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.
Díaz-Uriarte R, Al-Shahrour F, Dopazo J. Use of GO Terms to Understand the Biological Significance of Microarray Differential Gene Expression Data. In: Microarray data analysis III. Microarray data analysis III. Kluwer Academic, K. F. Johnson and S. M. Lin; 2003:233-247.
Desoignies N, Carbonell J, Moreau J-S, Conesa A, Dopazo J, Legrève A. Molecular interactions between sugar beet and Polymyxa betae during its life cycle. Annals of Applied Biology. 2014;164:244–256. doi:10.1111/aab.12095.
Del Pozo MGonzález-, Bravo-Gil N, Méndez-Vidal C, et al. Re-evaluation casts doubt on the pathogenicity of homozygous USH2A p.C759F. Am J Med Genet A. 2015;167(7):1597-600. doi:10.1002/ajmg.a.37003.
del Pozo MGonzález-, Méndez-Vidal C, Bravo-Gil N, et al. Exome sequencing reveals novel and recurrent mutations with clinical significance in inherited retinal dystrophies. PLoS One. 2014;9(12):e116176. doi:10.1371/journal.pone.0116176.
del Pozo MGonzález-, Méndez-Vidal C, Santoyo-López J, et al. Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet-Biedl family. Mol Genet Genomic Med. 2014;2(2):124-33. doi:10.1002/mgg3.50.
del Pozo MGonzález-, Méndez-Vidal C, Santoyo-López J, et al. Deciphering intrafamilial phenotypic variability by exome sequencing in a Bardet–Biedl family. Molecular Genetics & Genomic Medicine. 2014;2:124-133. doi:10.1002/mgg3.50.
del Pozo MGonzález-, Borrego S, Barragán I, et al. Mutation screening of multiple genes in Spanish patients with autosomal recessive retinitis pigmentosa by targeted resequencing. PLoS One. 2011;6(12):e27894. doi:10.1371/journal.pone.0027894.
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.
de Castro-Miró M, Pomares E, Lorés-Motta L, et al. Combined genetic and high-throughput strategies for molecular diagnosis of inherited retinal dystrophies. PloS one. 2014;9:e88410. doi:10.1371/journal.pone.0088410.
De Baets G, Van Durme J, Reumers J, et al. SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants. Nucleic Acids Res. 2012;40(Database issue):D935-9. doi:10.1093/nar/gkr996.
De Baets G, Reumers J, Blanco JDelgado, Dopazo J, Schymkowitz J, Rousseau F. An evolutionary trade-off between protein turnover rate and protein aggregation favors a higher aggregation propensity in fast degrading proteins. PLoS computational biology. 2011;7:e1002090. doi:10.1371/journal.pcbi.1002090.
C
Cuenca-Bono B, García-Molinero V, Pascual-García P, et al. SUS1 introns are required for efficient mRNA nuclear export in yeast. Nucleic acids research. 2011;39:8599-611.
Cubuk C, Loucera C, Peña-Chilet M, Dopazo J. Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer. Int J Mol Sci. 2023;24(8). doi:10.3390/ijms24087450.
Cubuk C, Hidalgo MR, Amadoz A, et al. Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models. NPJ Syst Biol Appl. 2019;5:7. doi:10.1038/s41540-019-0087-2.
Cubuk C, Hidalgo MR, Amadoz A, et al. Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape. Cancer Res. 2018;78(21):6059-6072. doi:10.1158/0008-5472.CAN-17-2705.
Cubuk C, Can FE, Peña-Chilet M, Dopazo J. Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments. Cells. 2020;9(7). doi:10.3390/cells9071579.
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.
Mapping the human genetic architecture of COVID-19. Nature. 2021;600(7889):472-477. doi:10.1038/s41586-021-03767-x.
A second update on mapping the human genetic architecture of COVID-19. Nature. 2023;621(7977):E7-E26. doi:10.1038/s41586-023-06355-3.
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.