OUR RESEARCH PROVIDES NEW CHARACTERIZATION METHODS AND VALUABLE TOOLS.
The Bioinformatics and Biostatistics Unit (the UBB in it’s Spanish acronym) is a technical and scientific unit which is involved in several different research activities including:
The development and application of big-data analysis methods in biomedical studies.
- One of our main projects involves the characterization of sex differences in health and disease by using meta-analysis techniques to analyze ‘–omic’ data. The development and application of computational approaches derived from these analyses have allowed us to detect and characterize the specific molecular mechanisms driving cardiovascular diseases (aortic stenosis and ischemic heart disease), neurodegenerative diseases (Parkinson’s and Alzheimer’s), and different tumor groups, both in men and women.
- Our work also tries to detect and understand the molecular mechanisms associated with spinal cord injuries. In one project, we carried out a systematic review and meta-analysis of every published transcriptomic study related to spinal lesions at the functional level. This allowed us to better characterize these injuries and to determine the common mechanisms implicated in treatments shown to improve this damage across different species.
- Another area of particular interest is the identification of precision immunotherapy biomarkers. By studying previously published tumor mutation loads, mutation signatures, and markers associated with better responses to immunotherapy treatments, we uncovered differential expression profiles according to the cancer type and patient sex.
Clinical predictors based on high-performance technologies and artificial intelligence methods.
- We are currently working to develop tools to detect early-stage tumors via liquid biopsy samples by using multi-omic classifiers.
- In other projects we are integrating omic data and biomedical imaging to generate tools that can predict the risk of neurodegenerative disorders such as Alzheimer’s or Parkinson’s disease in different individuals.
Get to know us better
The people who make it all possible
Francisco García García
Marta Rosa Hidalgo García
Rubén Sánchez García
José Francisco Catalá Senent
Rubén Grillo Risco
Our scientific contributions
Hepatic steatosis and steatohepatitis: a functional meta-analysis of sex-based differences in transcriptomic studies.
Català-Senent JF, Hidalgo MR, Berenguer M, Parthasarathy G, Malhi H, Malmierca-Merlo P, de la Iglesia-Vayá M and García-García F
Biology of Sex Differences, 2021 Mar,  DOI:  10.1186/s13293-021-00368-1,  Vol. 12,  pag. 29-29
Functional Signatures in Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Sex-Based Differences in Transcriptomic Studies
I. PEREZ-DIEZ, M. HIDALGO, P. MALMIERCA-MERLO, Z. ANDREU, S. ROMERA-GINER, R. FARRAS, M. DE LA IGLESIA-VAYA, M. PROVENCIO, A. ROMERO and F. GARCIA-GARCIA
Cancers, 2021 Jan,  DOI:  10.3390/cancers13010143,  Vol. 13,  pag. 143
Unveiling Sex-Based Differences in the Effects of Alcohol Abuse: A Comprehensive Functional Meta-Analysis of Transcriptomic Studies.
Casanova Ferrer F, Pascual M, Hidalgo MR, Malmierca-Merlo P, Guerri C and García-García F
Genes, 2020 Sep,  DOI:  10.3390/genes11091106,  Vol. 11,  pag. 1106
Sex is a strong prognostic factor in stage IV non-small-cell lung cancer patients and should be considered in survival rate estimation.
Barquín M, Calvo V, García-García F, Nuñez B, Sánchez-Herrero E, Serna-Blasco R, Auglyte M, Carcereny E, Rodriguez-Abreu D, López Castro R, Guirado M, Camps C, Bosch-Barrera J, Massuti B, Ortega AL, Del Barco E, Gonzalez-Larriba JL, Aguiar D, García-Campelo R, Dómine M, Agraso S, Sala MA, Oramas J, Bernabé R, Blanco R, Parejo C, Cruz A, Menasalvas E, Royuela A, Romero A and Provencio M
Cancer Epidemiology, 2020 Aug,  DOI:  10.1016/j.canep.2020.101737,  Vol. 67,  pag. 101737-101737
Gender differences in the inflammatory cytokine and chemokine profiles induced by binge ethanol drinking in adolescence
M. PASCUAL, J. MONTESINOS, M. MARCOS, J. TORRES, P. COSTA-ALBA, F. GARCIA-GARCIA, F. LASO and C. GUERRI
ADDICTION BIOLOGY, 2017 Nov,  DOI:  10.1111/adb.12461,  Vol. 22,  pag. 1829-1841