Pipeline development to computational analysis of preteomics data

• Grant number: 13/22801-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2014
• End date: December 31, 2015
• Field of knowledge: Health Sciences - Dentistry
• Principal Investigator: Adriana Franco Paes Leme
• Grantee: Mateus Augusto Bellomo Agrello Ruivo
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia e Inovação (Brasil). Campinas , SP, Brazil

Abstract

In contemporary biology, the development of technologies and methods to identify e quantify proteins become a important question to understanding of biological systems. The mass spectrometry usage has been adopted as pattern to protein identification and now provides the basis to absolute and relative quantification of peptides and proteins, being the broader and most versatile tool in large-scale proteomics. The need to characterize changes in gene expression at protein level has led to development of different methodologies of quantification. Each time a new experimental method is developed in proteomics, new algorithms to interpretation of data also need to be deployed. Therefore, in many situations data analysis became fragmented since the existing programs cover only a share of methods, leading the researchers to look for compatible tools to continue with analysis. In this context it is necessary the development of automated and standardized workflows (pipelines) for analysis of several proteomicd experiments, that can cover the increasing demand in this field, comprising the following steps: (I) raw data processing generated by large-scale experiments in mass spectrometer, (II) wide and robust statistical analysis of data, (III) complete annotation of data, and (IV) integration of analyzed data in biological interaction network. By this, we propose in this project develop a pipeline that allow us accomplish the proteomics data analysis in automated way and will be offer without a cost to general community through web platform.