Abstract
The development of high-throughput techniques in biology is transforming biology in a data-rich discipline. We will consider in this project integrated biological networks: these networks deal with all the gene interactions mediated by metabolism, regulation and protein-protein interactions. We will deploy machine learning tools that will use topological data from these graphs, expression data, genomic organization and cellular localization to extract relevant biological information such as detection of drug target genes, morbid genes for humans or essential genes for bacteria. In this project we will use these information to investigate the influence of topological properties on synthetic lethality and conditionally essential genes. (AU)
Scientific publications
(7)
(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)
POLLO-OLIVEIRA, LETICIA;
POST, HARM;
ACENCIO, MARCIO LUIS;
LEMKE, NEY;
VAN DEN TOORN, HENK;
TRAGANTE, VINICIUS;
HECK, ALBERT J. R.;
ALTELAAR, A. F. MAARTEN;
YATSUDA, ANA PATRICIA.
Unravelling the Neospora caninum secretome through the secreted fraction (ESA) and quantification of the discharged tachyzoite using high-resolution mass spectrometry-based proteomics.
PARASITES & VECTORS,
v. 6,
NOV 23 2013.
Web of Science Citations: 8.
CAMILO, ESTHER;
BOVOLENTA, LUIZ A.;
ACENCIO, MARCIO L.;
RYBARCZYK-FILHO, JOSE L.;
CASTRO, MAURO A. A.;
MOREIRA, JOSE C. F.;
LEMKE, NEY.
GALANT: a Cytoscape plugin for visualizing data as functional landscapes projected onto biological networks.
Bioinformatics,
v. 29,
n. 19,
p. 2505-2506,
OCT 1 2013.
Web of Science Citations: 3.