Biomedical Data Analysis

Data Mining refers to the application of statistical and computing techniques in order to assist the extraction of potentially interesting and synthetic knowledge from large volumes of raw data. Potential applications in the biomedical field include the automatic identification of candidate biomarkers for a disease or indicative of a treatment response, and the construction of diagnostic or prognostic rules exploiting these biomarkers.These methods being generic, they can be applied to various sources of data and biological/biomedical questions. During the last years, in close collaboration with GIGA researchers, we successfully applied such techniques to analyse proteomic data (protein expression profiles using SELDI-TOF protein chips) and genomic data (mRNAs profiles using gene chips, miRNAs using qRT-PCR, methylated CpG using methylation arrays), in the context of different projects, resulting in scientific publications* in journals such as Bioinformatics, Proteomics, Clinical Biochemistry, Clinical Chemistry, Arthritis and Rheumatism. Scholarly peer review is the process of subjecting an author's scholarlywork, research, or ideas to the scrutiny of others who are experts in the same field, before a paper describing this work is published in a journal. The work may be accepted, considered acceptable with revisions, or rejected. Peer review requires a community of experts in a given (narrowly defined) field, who are qualified and able to perform reasonably impartial review.
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Last date updated on September, 2014

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