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2018
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.
2017
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 Syst Biol. 2017;11(1):110. doi:10.1186/s12918-017-0495-0.
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.
Lopez J, Coll J, Haimel M, et al. HGVA: the Human Genome Variation Archive. Nucleic Acids Res. 2017;45(W1):W189-W194. doi:10.1093/nar/gkx445.
Hidalgo MR, Cubuk C, Amadoz A, Salavert F, Carbonell-Caballero J, Dopazo J. High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes. Oncotarget. 2017;8(3):5160-5178. doi:10.18632/oncotarget.14107.
Moschen S, Di Rienzo JA, Higgins J, et al. Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.). Plant Mol Biol. 2017;94(4-5):549-564. doi:10.1007/s11103-017-0625-5.
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.
Carbonell-Caballero J, Amadoz A, Alonso R, et al. Reference genome assessment from a population scale perspective: an accurate profile of variability and noise. Bioinformatics. 2017;33(22):3511-3517. doi:10.1093/bioinformatics/btx482.
Juanes JM, Gallego A, Tárraga J, et al. VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy. BMC Bioinformatics. 2017;18(1):421. doi:10.1186/s12859-017-1837-z.
Gui H, Schriemer D, Cheng WW, et al. Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes. Genome biology. 2017;18:48. doi:10.1186/s13059-017-1174-6.
Gui H, Schriemer D, Cheng WW, et al. Whole exome sequencing coupled with unbiased functional analysis reveals new Hirschsprung disease genes. Genome Biology. 2017;18(1). doi:10.1186/s13059-017-1174-6.
2016
Sanghez V, Cubuk C, Sebastián-Leon P, et al. Chronic subordination stress selectively downregulates the insulin signaling pathway in liver and skeletal muscle but not in adipose tissue of male mice. Stress (Amsterdam, Netherlands). 2016:1-11. doi:10.3109/10253890.2016.1151491.
Prieto J, León M, Ponsoda X, et al. Dysfunctional mitochondrial fission impairs cell reprogramming. Cell Cycle. 2016;15(23):3240-3250. doi:10.1080/15384101.2016.1241930.
Lagarde J, Uszczynska-Ratajczak B, Santoyo-López J, et al. Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq). Nature communications. 2016;7:12339. doi:10.1038/ncomms12339.
Lagarde J, Uszczynska-Ratajczak B, Santoyo-López J, et al. Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq). Nature Communications. 2016;7(1). doi:10.1038/ncomms12339.
Tárraga J, Gallego A, Arnau V, Medina I, Dopazo J. HPG pore: an efficient and scalable framework for nanopore sequencing data. BMC Bioinformatics. 2016;17(1). doi:10.1186/s12859-016-0966-0.
Tárraga J, Gallego A, Arnau V, Medina I, Dopazo J. HPG pore: an efficient and scalable framework for nanopore sequencing data. BMC bioinformatics. 2016;17:107. doi:10.1186/s12859-016-0966-0.
Bravo-Gil N, Méndez-Vidal C, Romero-Pérez L, et al. Improving the management of Inherited Retinal Dystrophies by targeted sequencing of a population-specific gene panel. Sci Rep. 2016;6:23910. doi:10.1038/srep23910.
Garcia-Garcia F, Panadero J, Dopazo J, Montaner D. Integrated gene set analysis for microRNA studies. Bioinformatics. 2016;32(18):2809-16. doi:10.1093/bioinformatics/btw334.
Moschen S, Luoni SBengoa, Di Rienzo JA, et al. Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower. Plant Biotechnol J. 2016;14(2):719-34. doi:10.1111/pbi.12422.