Evaluation and development of computational tools for the statistical analysis of proteomic data

• Grant number: 14/21445-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2014
• End date: November 30, 2015
• Field of knowledge: Biological Sciences - Biology
• Principal Investigator: Adriana Franco Paes Leme
• Grantee: Daniel Germano Travieso
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia e Inovação (Brasil). Campinas , SP, Brazil

Abstract

With the development of quantitative proteomics based on mass spectrometry, protein identification and classification of proteomics data appear as themes closely related and necessary for the interpretation of biological phenomena. However, technological advances in quantification of proteins was not directly followed by advances in data analysis. Currently, few research groups that exploit information proteome have the tools and skills necessary to perform all steps of the data analysis, which limits the interpretation of the phenomena studied. In this context, we aimed at the development and implementation of tools for the interpretation and analysis of proteomic data in order to broaden the gain of information quality and in respective analyzes performed today. Univariate statistical analysis, multivariate data normalization and data validations exemplify points of statistical analysis that need to be developed preferably automated way to improve the performance and quality of the whole process of data analysis. Thus, the development of scripts and integrated into workflows (pipelines) automated and standardized for statistical analysis of proteomic data functions becomes essential, since the demand for this type of analysis is growing, and few studies have been reported dealing on the application of different methods of statistical analysis of proteomic data.