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.
Presentation
Get to know us better
Research Staff
The people who make it all possible
Francisco García García
fgarcia@cipf.es
Marta Rosa Hidalgo García
mhidalgo@cipf.es
Rubén Sánchez García
rsanchez@cipf.es
Rubén Grillo Risco
rgrillo@cipf.es
José Francisco Catalá Senent
jfcatala@cipf.es
Publications
Our scientific contributions
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,  202 ,  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 ,  Vol. 67,  pag. 101737-101737
Rilpivirine attenuates liver fibrosis through selective STAT1-mediated apoptosis in hepatic stellate cells.
Martí-Rodrigo A, Alegre F, Moragrega ÁB, García-García F, Martí-Rodrigo P, Fernández-Iglesias A, Gracia-Sancho J, Apostolova N, Esplugues JV and Blas-García A
GUT,  201 ,  Vol. 69,  pag. 920-932
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 ,  Vol. 22,  pag. 1829-1841
Integrated gene set analysis for microRNA studies
F. GARCIA-GARCIA, J. PANADERO, J. DOPAZO and D. MONTANER
BIOINFORMATICS,  201 ,  Vol. 32,  pag. 2809-2816
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