| Grant number: | 14/09576-5 |
| Support Opportunities: | Regular Research Grants |
| Start date: | July 01, 2014 |
| End date: | September 30, 2016 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computational Mathematics |
| Principal Investigator: | André Fujita |
| Grantee: | André Fujita |
| Host Institution: | Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Associated researchers: | Alexandre Galvão Patriota ; Daniel Yasumasa Takahashi ; João Ricardo Sato ; Katlin Brauer Massirer ; Mário Henrique Bengtson |
Abstract
The understanding of the biological mechanisms underlying human diseases is one of the main challenges in biological sciences. Although several efforts, the large number of heterogeneous factors that influence the genesis of a disease makes it a very hard task. One of the challenges consists in understanding diseases by developing methods to statistically analyze and computationally manipulate huge scale data. This difficulty is generated by ultra large data size, heterogeneity, multidimensionality, and presence of intrinsic noise. In this context, the main aim of this project is the development of computational statistical techniques to infer the phenomena that emerges from the interactions of different biological components involved in diseases. In other words, we will develop formal statistical methods in graphs (hypothesis test, model selection, parameter estimator, etc) in order to compare neural networks obtained by the modeling of functional and structural resonance imaging data; and to integrate genomic, transcriptomic and phenotype in cancer. This will allow the modeling and integration of biological data obtained in diverse collaborations between our group and biomedical labs (Lab. of RNA and micro RNAs regulation in diseases (Prof. Massirer) and Lab. of Molecular Biology (Prof. Bengtson), both at UNICAMP; neuroscience data from Prof. Sato at UFABC and Dr. Takahashi of Princeton University) and consequently aid biomedical researchers to elucidate the mechanisms involved in several diseases, in particular, cancer, cardiovascular diseases, diabetes, and neural disorders. (AU)
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