Publications

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Iglesias JManuel, Beloqui I, Garcia-Garcia F, et al. Mammosphere formation in breast carcinoma cell lines depends upon expression of E-cadherin. PLoS One. 2013;8(10):e77281. doi:10.1371/journal.pone.0077281.
Iglesias JManuel, Beloqui I, Garcia-Garcia F, et al. Mammosphere Formation in Breast Carcinoma Cell Lines Depends upon Expression of E-cadherin. PLoS ONE. 2013;8:e77281 -. Available at: http://dx.doi.org/10.1371%2Fjournal.pone.0077281.
Carbonell J, Alloza E, Arce P, et al. A map of human microRNA variation uncovers unexpectedly high levels of variability. Genome medicine. 2012;4:62. doi:10.1186/gm363.
Mapping the human genetic architecture of COVID-19. Nature. 2021;600(7889):472-477. doi:10.1038/s41586-021-03767-x.
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.
Sánchez-Tena S, Reyes-Zurita FJ, Díaz-Moralli S, et al. Maslinic Acid-Enriched Diet Decreases Intestinal Tumorigenesis in Apc(Min/+) Mice through Transcriptomic and Metabolomic Reprogramming. PloS one. 2013;8:e59392. doi:10.1371/journal.pone.0059392.
Esteban-Medina M, Loucera C, Rian K, et al. The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery. J Transl Med. 2024;22(1):139. doi:10.1186/s12967-024-04911-7.
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.
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.
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.
Brumos J, Colmenero-Flores JM, Conesa A, et al. Membrane transporters and carbon metabolism implicated in chloride homeostasis differentiate salt stress responses in tolerant and sensitive Citrus rootstocks. Funct Integr Genomics. 2009. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19190944.
Sola-García A, Cáliz-Molina MÁngeles, Espadas I, et al. Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging. Commun Biol. 2023;6(1):250. doi:10.1038/s42003-023-04625-4.
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.
Mateos A, Herrero J, Tamames J, Dopazo J. Methods of Microarray Data Analysis IISupervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles. (Lin SM, Johnson KF, eds.). Boston: Kluwer Academic Publishers; 2002:91 - 103. doi:10.1007/b11298210.1007/0-306-47598-7_7.
Rizza S, Conesa A, Juarez J, et al. Microarray analysis of Etrog citron (Citrus medica L.) reveals changes in chloroplast, cell wall, peroxidase and symporter activities in response to viroid infection. Molecular plant pathology. 2012. doi:10.1111/j.1364-3703.2012.00794.x.
Dopazo J. Microarray Data Processing And Analysis. In: Microarray data analysis II. Microarray data analysis II. Kluwer Academic; 2002:43-63.
The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nature Biotechnology. 2010;28(8):827 - 838. doi:10.1038/nbt.1665.
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.
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.
Corrales P, Martin-Taboada M, Vivas-García Y, et al. microRNAs-mediated regulation of insulin signaling in white adipose tissue during aging: Role of caloric restriction. Aging Cell. 2023:e13919. doi:10.1111/acel.13919.
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.
Pieper U, Eswar N, Davis FP, et al. MODBASE: a database of annotated comparative protein structure models and associated resources. Nucleic Acids Res. 2006;34:D291-5. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16381869.
Pieper U, Eswar N, Webb BM, et al. MODBASE, a database of annotated comparative protein structure models and associated resources. Nucleic Acids Res. 2009;37:D347-54. Available at: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18948282.
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.