For the entire publication list, please follow the link.

See publications in review (available at bioRxiv):

  • Uncovering the cis-regulatory program of early human B-cell commitment and its implications in the pathogenesis of B-cell acute lymphoblastic leukemia Núria Planell, Xabier Martínez-de-Morentin, Daniel Mouzo, David Lara-Astiaso, Amaia Vilas-Zornoza, Patxi San Martín-Uriz, et al.
    bioRxiv 2023.07.01.547234; doi:

See below the selected publications:


  • Lasaga, M., Río, P., Vilas-Zornoza, A., Planell, N., Navarro, S., Alignani, D., Fernández-Varas, B., et al. Gene therapy restores the transcriptional program of hematopoietic stem cells in Fanconi anemia. Haematologica, 2023
  • Ainciburu, M., Ezponda, T., Berastegui, N., Alfonso-Pierola, A., Vilas-Zornoza, A., San Martin-Uriz, P., et al. Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single cell resolution. ELife, 2023 12, 1–28.
  • Khan, S. A., Lehmann, R., Martinez-de-Morentin, X., Maillo, A., Lagani, V., Kiani, N. A., Gomez-Cabrero, D., & Tegner, J. scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences. PloS ONE, 2023 18(2), 1–17.
  • Larrayoz, M. J. M., Garcia-Barchino, M. J., Celay, J., Etxebeste, A., Jimenez, M., Perez, C., et al. Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma. Nature Medicine, 2023 29(3), 2023 632–645.
  • Carr, V. R., Pissis, S. P., Mullany, P., Shoaie, S., Gomez-Cabrero, D., & Moyes, D. L. Palidis: fast discovery of novel insertion sequences. Microbial Genomics, 2023 9(3), 1–9.
  • Martinez-de-morentin, X., Khan, S. A., Lehmann, R., Qu, S., Maillo, A., Kiani, et al. LIBRA: an adaptative integrative tool for paired single-cell multi-omics data. Quantitative Biology. 2023


  • Moreno-Indias, I., Zomer, A. L., Gómez-Cabrero, D., & Claesson, M. J. Editorial: Microbiome and Machine Learning. Frontiers in Microbiology, 2022 13.
  • Tegner, J. N., & Gomez-Cabrero, D. Data-driven bioinformatics to disentangle cells within a tissue microenvironment. Trends in Cell Biology, 2022 32(6), 467–469.
  • Kular, L., Ewing, E., Needhamsen, M., Kakhki, M. P., Covacu, R., Gomez-Cabrero, D., Brundin, L., & Jagodic, M. DNA methylation changes in glial cells of the normal-appearing white matter in Multiple Sclerosis patients. Epigenetics, 2022 17(11), 1311–1330.
  • Kular, L., Klose, D., Urdánoz-Casado, A., Ewing, E., Planell, N., Gomez-Cabrero, D., Needhamsen, M., & Jagodic, M. Epigenetic clock indicates accelerated aging in glial cells of progressive multiple sclerosis patients. In Frontiers in aging neuroscience. 2022.
  • Magnusson, R., Rundquist, O., Kim, M. J., Hellberg, S., Na, C. H., Benson, M., et al. (2022). RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases. Frontiers in Molecular Biosciences, 2022 9(August), 1–13.


  • Planell N, Lagani V, Sebastian-Leon P, van der Kloet F, Ewing E, Karathanasis N, et al. STATegra: Multi-Omics Data Integration – A Conceptual Scheme With a Bioinformatics Pipeline. Front Genet. 2021;12:143.
  • Rad Pour S, Pico de Coana Y, Martinez de Morentin X, et al. Predicting anti-PD-1 responders in malignant melanoma from the frequency of S100A9+ monocytes in the blood. Journal for ImmunoTherapy of Cancer, 2021. to appear.
  • Elias S, Schmidt A, Gomez-Cabrero D, Tegner J. Gene regulatory network of human GM-CSF secreting T helper cells. Journal of Immunology Research. 2021; . doi:10.1101/555433
  • Moreno-Indias I, Lahti L, Nedyalkova M, Elbere I, Roshchupkin G, Adilovic M, et al. Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions . Front Microbiol. 2021;12:277
  • Gomez-Cabrero D, Walter S, Abugessaisa I, Miñambres-Herraiz R, Palomares LB, Butcher L, et al. A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts. GeroScience. 2021 DOI: 10.1007/s11357-021-00334-0 Frailomic Consortia paper
  • Butcher L, Carnicero JA, Pérès K, Colpo M, Gomez Cabrero D, Dartigues J-F, et al. Higher sRAGE Levels Predict Mortality in Frail Older Adults with Cardiovascular Disease. Gerontology. 2021 DOI: 10.1159/000512287


  • Ewing E, Planell-Picola N, Jagodic M, Gomez-Cabrero D. GeneSetCluster: a tool for summarizing and integrating gene-set analysis results. BMC Bioinformatics. 2020;21(1):443. link
  • Sumida N, Sifakis EG, Kiani NA, Ronnegren AL, Scholz BA, Vestlund J, et al. MYC as a driver of stochastic chromatin networks: implications for the fitness of cancer cells. Nucleic Acids Res. 2020. link
  • Ruiz-Villalba A, Romero JP, Hernandez SC, et al. Single-Cell RNA-seq Analysis Reveals a Crucial Role for Collagen Triple Helix Repeat Containing 1 (CTHRC1) Cardiac Fibroblasts after Myocardial Infarction. Circulation. 2020.
  • Tarazona S, Balzano-Nogueira L, Gómez-Cabrero D, Schmidt A, Imhof A, Hankemeier T, et al. Harmonization of quality metrics and power calculation in multi-omic studies. Nat Commun. Springer US; 2020;11: 1–13.
  • López-Vicario C, Checa A, Urdangarin A, Aguilar F, Alcaraz-Quiles J, Caraceni P, et al. Targeted lipidomics reveals extensive changes in circulating lipid mediators in patients with acutely decompensated cirrhosis. J Hepatol. 2020; 1–12.
  • Karlsson L, Barbaro M, Ewing E, Gomez-Cabrero D, Lajic S. Genome-wide investigation of DNA methylation in congenital adrenal hyperplasia. J Steroid Biochem Mol Biol. 2020; 105699. link.
  • Goren Saenz-Pipaon, Patxi San Martín, Núria Planell, Alberto Maillo, et al. (2020) Functional and transcriptomic analysis of extracellular vesicles identifies calprotectin as a new prognostic marker in peripheral arterial disease (PAD). 2020 Journal of Extracellular Vesicles, 9:1, 1729646. link
  • Carr VR, Witherden E, Lee S, Shoaie S, Mullany P, Proctor GB, et al. Abundance and diversity of resistomes differ between healthy human oral cavities and gut. Nature Communications; 2020; 11:693. link
  • Rad Pour S, Morikawa H, Kiani NA, Gomez-Cabrero D, Hayes A, Zheng X, et al. Immunometabolic Network Interactions of the Kynurenine Pathway in Cutaneous Malignant Melanoma. Front Oncol. 2020;10: 51. link


  • Jansen C, Ramirez RN, El-Ali NC, Gomez-Cabrero D, Tegner J, Merkenschlager M, et al. Building gene regulatory networks from scATAC-seq and scRNA-seq using Linked Self-Organizing Maps. PLOS Comput Biol. 2019;15: 438937. doi:10.1101/438937
  • Gomez-Cabrero D, Tarazona S, Ferreirós-Vidal I, Ramirez RN, Company C, Schmidt A, et al. STATegra: a comprehensive multi-omics dataset of B-cell differentiation in mouse. Scientific Data; 2019, to appear; 587477. doi:10.1101/587477
  • International Multiple Sclerosis Genetics Consortium, Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility, Science, 2019, 365:6460.
  • Fernandes SJ, Morikawa H, Ewing E, Ruhrmann S, Joshi RN, Lagani V, et al. Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients. Scientific Reports; 2019;9: 11996. doi:10.1038/s41598-019-48493-7
  • Kular L, Needhamsen M, Adzemovic MZ, Kramarova T, Gomez-Cabrero D, Ewing E, et al. Neuronal methylome reveals CREB-associated neuro-axonal impairment in multiple sclerosis. Clin Epigenetics. 2019;11: 86. doi:10.1186/s13148-019-0678-1
  • Gossec L, Kedra J, Servy H, Pandit A, Stones S, Berenbaum F, et al. EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases. Ann Rheum Dis. 2019;  doi:10.1136/annrheumdis-2019-215694
  • Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, et al. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun. 2019;10: 2674. doi:10.1038/s41467-019-09799-2
  • Butcher L, Carnicero JA, Gomez Cabrero D, Dartigues J-F, Pérès K, Garcia-Garcia FJ, et al. Increased levels of soluble Receptor for Advanced Glycation End-products (RAGE) are associated with a higher risk of mortality in frail older adults. Age Ageing. 2019; 1–7. doi:10.1093/ageing/afz073
  • Carlström KE, Ewing E, Granqvist M, Gyllenberg A, Aeinehband S, Enoksson SL, et al. Therapeutic efficacy of dimethyl fumarate in relapsing-remitting multiple sclerosis associates with ROS pathway in monocytes. Nat Commun. Springer US; 2019;10: 3081. doi:10.1038/s41467-019-11139-3
  • Ferreirós-Vidal I, Carroll T, Zhang T, Lagani V, Ramirez RN, Ing-Simmons E,… , Gomez-Cabrero D. Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation. PLOS Biol. 2019;17.
  • Ewing E, Kular L, Fernandes SJ, Karathanasis N, Lagani V, Ruhrmann S, …, Gomez-Cabrero D*, Jagodic M*. Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression. EBioMedicine. 2019.
  • Pilleron S, Weber D, Pérès K, Colpo M, Gomez-Cabrero D, Stuetz W, et al. Patterns of circulating fat-soluble vitamins and carotenoids and risk of frailty in four European cohorts of older adults. Eur J Nutr. Springer Berlin Heidelberg; 2019;58: 379–389.
  • Joshi et al. Phosphatase inhibitor PPP1R11 modulates resistance of human T cells toward Treg‐mediated suppression of cytokine expression. J Leukoc Biol. 2019.
  • Karlsson L, Barbaro M, Ewing E, Gomez-Cabrero D*, Lajic S*; Epigenetic Alterations Associated With Early Prenatal Dexamethasone Treatment, Journal of the Endocrine Society, 2019; 3:1 pp. 250–263, link
  • Magnusson R, Rundquist O, Kim MJ, Hellberg S, Na CH, Benson M, et al. On the prediction of protein abundance from RNA. bioRxiv. Cold Spring Harbor Laboratory; 2019; 599373. doi:10.1101/599373


  • Kular et al, DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in Multiple Sclerosis. Nat. Communications, 2018; 9 article number 2397.
  • Tényi Á, Vela E, Cano I, Cleries M, Monterde D, Gomez-Cabrero D*, Roca J*, Risk and temporal order of disease diagnosis of comorbidities in patients with COPD: a population health perspective BMJ Open Respiratory Research 2018;5:e000302. doi: 10.1136/bmjresp-2018-000302
  • Schmidt, A. et al. Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg ) differentiation reveals novel regulators of FOXP3. BMC Biology. 2018; 16:47 pp.1–35.
  • James T, Linde M, Morikawa H, Fernandes SJ, Ruhrmann S, Huss M, …, Gomez-Cabrero D*, Kockum I*. Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients. Hum Mol Genet. 2018;0: 1–17. doi:10.1093/hmg/ddy001
  • Tényi Á, Cano I, Marabita F, Kiani N, Kalko SG, Barreiro E, …, Gomez-Cabrero D*, Roca J*. Network modules uncover mechanisms of skeletal muscle dysfunction in COPD patients. J Transl Med. BioMed Central; 2018;16: 34. doi:10.1186/s12967-018-1405-y
  • Pilleron, S. et al., Patterns of circulating fat-soluble vitamins and carotenoids and risk of frailty in four European cohorts of older adults. 2018. European Journal of Nutrition.


  • Ramos M, Schiffer L, Re A, Azhar R, Basunia A, Rodriguez C, et al. Software for the Integration of Multiomics Experiments in Bioconductor. Cancer Res. 2017;77: e39–e42. doi:10.1158/0008-5472.CAN-17-0344
  • Needhamsen M, Ewing E, Lund H, Gomez-Cabrero D, Harris RARA, Kular L, et al. Usability of human Infinium MethylationEPIC BeadChip for mouse DNA methylation studies. BMC Bioinformatics.  2017;18: 486. doi:10.1186/s12859-017-1870-y
  • Sabrina Ruhrmann, Ewoud Ewing, Eliane Piket, Lara Kular, Julio Cesar Cetrulo Lorenzi, Sunjay Jude Fernandes, et al. Hypermethylation of MIR21 in CD4+ T cells from patients with relapsing-remitting multiple sclerosis associates with lower miRNA-21 levels and concomitant up-regulation of its target genes. Mult Scler J. 2017;8: 1+13. doi:10.1177/135245
  • Gomez-Cabrero D, Tegnér J. Iterative Systems Biology for Medicine – Time for advancing from network signatures to mechanistic equations. Curr Opin Syst Biol. 2017;3: 111–118. doi:10.1016/j.coisb.2017.05.001


  • Gomez-Cabrero D, Menche J, Vargas C, Cano I, Maier D, Barabási A-LA-L, et al. From comorbidities of chronic obstructive pulmonary disease to identification of shared molecular mechanisms by data integration. BMC Bioinformatics. 2016;17: 441. doi:10.1186/s12859-016-1291-3
  • Lagani V, Karozou AD, Gomez-Cabrero D, Silberberg G, Tsamardinos I. A comparative evaluation of data-merging and meta-analysis methods for reconstructing gene-gene interactions. BMC Bioinformatics. 2016;17: 194. doi:10.1186/s12859-016-1038-1
  • Kannan L, Ramos M, Re A, El-Hachem N, Safikhani Z, et al. Public data and open source tools for multi-assay genomic investigation of disease. Brief Bioinform. 2016;17: 603–615. doi:10.1093/bib/bbv080
  • Gomez-Cabrero D, Almgren M, Sjöholm LKLK, Hensvold AHAH, Ringh MVM V., Tryggvadottir R, et al. High-specificity bioinformatics framework for epigenomic profiling of discordant twins reveals specific and shared markers for ACPA and ACPA-positive rheumatoid arthritis. Genome Med. Genome Medicine; 2016;8: 124. doi:10.1186/s13073-016-0374-0
  • Kannan V, Swartz F, Kiani NANA, Silberberg G, Tsipras G, Gomez-Cabrero D, et al. Conditional Disease Development extracted from Longitudinal Health Care Cohort Data using Layered Network Construction. Scientific Reports. 2016;6: 1–14. doi:10.1038/srep26170
  • Tényi Á, de Atauri P, Gomez-Cabrero D, Cano I, Clarke K, Falciani F, et al. ChainRank, a chain prioritisation method for contextualisation of biological networks. BMC Bioinformatics. 2016;17: 17. doi:10.1186/s12859-015-0864-x


  • Rodríguez-Cortez VCVC, del Pino-Molina L, Rodríguez-Ubreva J, Ciudad L, Gómez-Cabrero D, Company C, et al. Monozygotic twins discordant for common variable immunodeficiency reveal impaired DNA demethylation during naïve-to-memory B-cell transition. Nature Communications. 2015;6: 7335. doi:10.1038/ncomms8335
  • Danielsson F, James T, Gomez-Cabrero D, Huss M. Assessing the consistency of public human tissue RNA-seq data sets. Briefings in Bioinformatics. 2015;16: 941–949. doi:10.1093/bib/bbv017
  • Lippi G, Jansen-Duerr P, Viña J, Durrance-Bagale A, Abugessaisa I, Gomez-Cabrero D, et al. Laboratory biomarkers and frailty: Presentation of the FRAILOMIC initiative. Clin Chem Lab Med. 2015;53: e253–e255. doi:10.1515/cclm-2015-0147


  • Cano-Colino M, Almeida R, Gomez-Cabrero D, Artigas F, Compte A. Serotonin regulates performance nonmonotonically in a spatial working memory network. Cereb Cortex. 2014;24: 2449–2463. doi:10.1093/cercor/bht096
  • Lindholm ME, Marabita F, Gomez-Cabrero D, Rundqvist H, Ekstrom TJ, Tegner J, et al. An integrative analysis reveals coordinated reprogramming of the epigenome and the transcriptome in human skeletal muscle after training. Epigenetics. 2014;9: 1557–1569. doi:10.4161/15592294.2014.982445
  • Miralles F, Gomez-Cabrero D, Lluch-Ariet M, Tegnér J, Cascante M, Roca J, et al. Predictive medicine: outcomes, challenges and opportunities in the Synergy-COPD project. J Transl Med. BioMed Central Ltd; 2014;12 Suppl 2: S12. doi:10.1186/1479-5876-12-S2-S12
  • Gomez-Cabrero D, Menche J, Cano I, Abugessaisa I, Huertas-Migueláñez M, Tenyi A, et al. Systems Medicine: from molecular features and models to the clinic in COPD. J Transl Med. BioMed Central Ltd; 2014;12 Suppl 2: S4. doi:10.1186/1479-5876-12-S2-S4
  • Gomez-Cabrero D, Lluch-Ariet M, Tegnér J, Cascante M, Miralles F, Roca J. Synergy-COPD: a systems approach for understanding and managing chronic diseases. J Transl Med. BioMed Central Ltd; 2014;12 Suppl 2: S2. doi:10.1186/1479-5876-12-S2-S2
  • Snir O*, Gomez-Cabrero D*, Montes A, Perez-Pampin E, Gómez-Reino JJ, Seddighzadeh M, et al. Non-HLA genes PTPN22, CDK6 and PADI4 are associated with specific autoantibodies in HLA-defined subgroups of rheumatoid arthritis. Arthritis Res Ther. 2014;16: 414. doi:10.1186/s13075-014-0414-3
  • Gomez-Cabrero D, Abugessaisa I, Maier D, Teschendorff A, Merkenschlager M, Gisel A, et al. Data integration in the era of omics: current and future challenges. BMC Syst Biol. BioMed Central Ltd; 2014;8 Suppl 2: I1. doi:10.1186/1752-0509-8-S2-I1

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2013 and before (selected manuscripts)

  • Rodríguez-Ubreva, J. et al., 2011. Pre-B cell to macrophage transdifferentiation without significant promoter DNA methylation changes. Nucleic Acids Research, (10), pp.1–15.
  • Gomez-Cabrero, D., Compte, A. & Tegner, J., 2011. Workflow for generating competing hypothesis from models with parameter uncertainty. Interface Focus, 1(3), pp.438–449.
  • Taccioli, C. et al., 2011. ParkDB: a Parkinson’s disease gene expression database. Database : the journal of biological databases and curation, 2011, p.bar007.

Operations Research. Before 2010 (selected manuscripts).

  • Valls, V., Gomez-Cabrero, D., Perez, A., Quintanilla, S., 2007. Project Scheduling Optimization in Service Centre Management. Tijdschrift voor Economie en Management, LII(3), pp.341–366.
  • Gomez-Cabrero, D., Ranasinghe, D.N., , 2006, Fine-tuning the Ant Colony System algorithm through Particle Swarm Optimization. 2006 paper. Presented in conference. Technical report in “Universitat de Valencia”. Link at: