Expression of genes related to apoptosis, cell cycle and signaling pathways are independent of TP53 status in urinary bladder cancer cells

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

Prospecting major genes in dairy buffaloes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identificação de genes candidatos à indução do florescimento em cana-de-açúcar em câmara de fotoperíodo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Gene flow networks among American Aedes aegypti populations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Coordinated, network-based research as a strategic component of science in Brazil

Scientific research plays a fundamental role in the health and development of any society, since all technological advances depend ultimately on scientific discovery and the generation of wealth is intricately dependent on technological advance. Due to their importance, science and technology generally occupy important places in the hierarchical structure of developed societies, and they receive considerable public and private investment. Publicly funded science is almost entirely devoted to discovery, and it is administered and structured in a very similar way throughout the world. Particularly in the biological sciences, this structure, which is very much centered on the individual scientist and his own hypothesis-based investigations, may not be the best suited for either discovery in the context of complex biological systems, or for the efficient advancement of fundamental knowledge into practical utility. The adoption of other organizational paradigms, which permit a more coordinated and interactive research structure, may provide important opportunities to accelerate the scientific process and further enhance its relevance and contribution to society. The key alternative is a structure that incorporates larger organizational units to tackle larger and more complex problems. One example of such a unit is the research network. Brazil has utilized such networks to great effect in genome sequencing projects, demonstrating their relevance to the Brazilian research community and opening the possibility of their wider utility in the future.

Detecção do operon ica da produção de biofilme, gene mecA de resistência à oxacilina e identificação de espécies de Staphylococcus spp. diretamente dos frascos de hemoculturas pela técnica de PCR multiplex

Pós-graduação em Doenças Tropicais - FMB

Molecular investigation of zoonotic genotypes of Giardia intestinalis isolates in humans, dogs and cats, sheep, goats and cattle in Araçatuba (Sãoo Paulo State, Brazil) by the analysis of beta-giardin gene fragments

In the period from July 2009 to October 2010, fecal samples from 61 animals and 154 humans from the municipality of Aracatuba (São Paulo State, Brazil) were studied. Fecal samples from animals were collected in the Municipal Animal Shelter and the Veterinary Hospital of the Universidade Estadual Paulista. Human fecal specimens were collected in playschools in the outskirts of the city by the private network of clinical analysis laboratories of the municipal. Diagnosis was done by optical microscopy using the Faust and Hoffmann, Pons and Janer techniques. The genotypes of Giardia intestinalis were characterized by PCR-RFLP and confirmed by sequencing the ß-giardin gene. Human specimens were positive in 25.3% (39/154) of the cases with 26.8% (36/134) of the specimens from children and 15% (3/20) from adults being positive. The frequency of G. intestinalis among the animals was 23.0% (14/61). A total of 32 isolates of G. intestinalis obtained from human feces and six from dogs and cats were characteristic of the A genotype (AI and AII/AIII). The results of this study in respect to frequency of giardiasis are similar to reported in most studies in Brazil. The prevalence observed in animal populations conforms to worldwide infection rates. G. intestinalis genotypes considered zoonotic were detected in both pets and humans from the city of Aractuba, suggesting a possible zoonotic transmission of the parasite in the northwestern region of São Paulo State. The absence of these genotypes in farm animals may imply that they are not involved in the chain of transmission to humans in this region.

Análise de pathway e network em tecido adiposo in vivo e o papel da vitamina D na adipogênese in vitro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)