The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab)
was opened in January 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&C").
Since then, Dr. Claudia Angelini is coordinating the research team.
Our research activities have been always motivated by real problems arising in Physics, Medicine and Biology. In particular, we have focused on the analysis of high-throughput data by means of both statistical and computational methods. Our experience includes Bayesian inference, Denoising, Dimension reduction techniques, Functional data analysis, Multiple hypothesis testing, Multivariate statistics, Non-parametric regression, Supervised and Unsupervised learning, Variable selection, and Wavelets. More recently, the interest has been deeply focused on the high-dimensional data problems arising in genomics. We have worked on a variety of problems in statistical genomics, including methods for analysis of microarray time course gene expression data, methods for the identification of transcription factor binding sites using variable selection approaches, and methods for analysis of Next Generation Sequencing Data. Current activities of BioinfoLab involve the development of statistical methods and tools for next generation sequencing with application to Epigenomics and Transcriptomics.
HORIZON 2020/Marie Sklodowska Curie Action: INnovative Life sCIence Phd Programme in South Italy — INCIPIT
Progetto Bandiera Epigenomica:
Bioinformatics platform for integration of epigenomics data and systems biology.
Progetto Bandiera InterOmics:
Development of an integrated platform for the application of "omic" sciences to biomarker definition and theranostic, predictive and diagnostic profiles.
PONa3_00025: BIOforIU Infrastruttura multidisciplinare per lo studio e la valorizzazione della Biodiversita marina e terrestre nella prospettiva della Innovation Union.
COST Action BM1006: Next Generation Sequencing Data Analysis Network
INT.P02: CNR inter-departement project:
IAC Unit: Mathematical and Statistical Methods for genetics and proteomics
PON01_02460: Studio per la realizzazione di un presidiodiagnostico per l'individuazione distrategie terapeutiche personalizzate peril diabete di tipo 2 mediante approcci di genomica e trascrittomica.
CNR-RSTL n.26: Metodi Bayesiani di selezione delle variabili con applicazioni alla genomica.