Export 444 results:
Author Title Type [ Year(Asc)]
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.
Amadoz A, Hidalgo MR, Cubuk C, Carbonell-Caballero J, Dopazo J. A comparison of mechanistic signaling pathway activity analysis methods. Brief Bioinform. 2019;20(5):1655-1668. doi:10.1093/bib/bby040.
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.
Esteban-Medina M, Peña-Chilet M, Loucera C, Dopazo J. Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models. BMC Bioinformatics. 2019;20(1):370. doi:10.1186/s12859-019-2969-0.
Chacón-Solano E, León C, Díaz F, et al. Fibroblast activation and abnormal extracellular matrix remodelling as common hallmarks in three cancer-prone genodermatoses. Br J Dermatol. 2019;181(3):512-522. doi:10.1111/bjd.17698.
Martin-Broto J, Stacchiotti S, Lopez-Pousa A, et al. Pazopanib for treatment of advanced malignant and dedifferentiated solitary fibrous tumour: a multicentre, single-arm, phase 2 trial. Lancet Oncol. 2019;20(1):134-144. doi:10.1016/S1470-2045(18)30676-4.
Gómez-López G, Dopazo J, Cigudosa JC, Valencia A, Al-Shahrour F. Precision medicine needs pioneering clinical bioinformaticians. Brief Bioinform. 2019;20(3):752-766. doi:10.1093/bib/bbx144.
Perez-Gil D, Lopez FJ, Dopazo J, Marin-Garcia P, Rendon A, Medina I. PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources. BMC Bioinformatics. 2019;20(1):159. doi:10.1186/s12859-019-2726-4.
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.
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.
Wu GAlbert, Terol J, Ibañez V, et al. Genomics of the origin and evolution of Citrus. Nature. 2018;554(7692):311-316. doi:10.1038/nature25447.
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.
Hidalgo MR, Amadoz A, Cubuk C, Carbonell-Caballero J, Dopazo J. Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome. Biol Direct. 2018;13(1):16. doi:10.1186/s13062-018-0219-4.
Ibáñez M, Carbonell-Caballero J, Such E, et al. The modular network structure of the mutational landscape of Acute Myeloid Leukemia. PLoS One. 2018;13(10):e0202926. doi:10.1371/journal.pone.0202926.
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.PDF icon Roca-Ayats-2017NEJM - GGPS1 Mutation and Atypical Femoral Fractures with Bisphosphonates.pdf (214.03 KB)
Gil-Ibañez P, Garcia-Garcia F, Dopazo J, Bernal J, Morte B. Global Transcriptome Analysis of Primary Cerebrocortical Cells: Identification of Genes Regulated by Triiodothyronine in Specific Cell Types. Cereb Cortex. 2017;27(1):706-717. doi:10.1093/cercor/bhv273.
Dopazo J, Erten C. Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes. BMC Systems Biology. 2017;11(1). doi:10.1186/s12918-017-0495-0.
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.