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In silico construction of integrated molecular networks encompassing cell cycle regulation by extracellular matrix adhesion in Homo sapiens

Grant number: 07/01213-7
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): March 01, 2008
Effective date (End): March 31, 2011
Field of knowledge:Biological Sciences - Biophysics - Biophysics of Processes and Systems
Principal Investigator:Ney Lemke
Grantee:Marcio Luis Acencio
Host Institution: Instituto de Biociências (IBB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil


The reductionist approach has been effective in explaining the functioning of several biological processes. However, these processes have been shown to be extremely complex and to have emergent properties that cannot be explained, or even predicted, by such approach. To overcome these limitations, researches have adopted the systems biology approach, a new biology field that investigate how properties emerge from the nonlinear interaction of multiple components of biological processes. These interactions can be represented by a mathematical object called graph or network, where interacting elements are represented by nodes and interactions are represented by edges connecting pairs of nodes. In this project, we propose the in silico constructions of a molecular integrated network encompassing the regulation of cell cycle by extracellular matrix adhesion in H. sapiens. In most cells, cell cycle progression is normally dependent on adhesion to extracellular matrix, but no longer after oncogenic transformation. So, malignant cells are able to proliferate without anchorage to extracellular matrix. This ability is one of the fundamental properties of malignant cells and is a prerequisite for their metastatic capabilities. As metastasis is ultimately responsible for the great majority of cancer deaths, a nonlinear, systemically analysis of the adhesion control of cell cycle is needed for a better comprehension of this process and determination of appropriate drug targets capable to inhibit and/or perturb this system in a such way that side effects occur at a minimum rate. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
COSTA‚ P.R.; ACENCIO‚ M.L.; LEMKE‚ N.. A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data. BMC Genomics, v. 11, n. Suppl 5, p. S9, . (07/02827-9, 07/01213-7, 07/08466-8)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
ACENCIO, Marcio Luis. Construção e análise da rede integrada de interações entre genes humanos envolvida com a regulação da trnsição G1/S do ciclo celular plea adesão à matriz extracelular. 2011. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Instituto de Biociências. Botucatu Botucatu.

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