Transcriptomics and systems biology analysis in identification of specific pathways involved in cacao resistance and susceptibility to witches' broom disease

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exploring the multifactorial nature of autism through computational systems biology: Calcium and the Rho GTPase RAC1 under the spotlight

Autism is a neurodevelopmental disorder characterized by impaired social interaction and communication accompanied with repetitive behavioral patterns and unusual stereotyped interests. Autism is considered a highly heterogeneous disorder with diverse putative causes and associated factors giving rise to variable ranges of symptomatology. Incidence seems to be increasing with time, while the underlying pathophysiological mechanisms remain virtually uncharacterized (or unknown). By systematic review of the literature and a systems biology approach, our aims were to examine the multifactorial nature of autism with its broad range of severity, to ascertain the predominant biological processes, cellular components, and molecular functions integral to the disorder, and finally, to elucidate the most central contributions (genetic and/or environmental) in silico. With this goal, we developed an integrative network model for gene-environment interactions (GENVI model) where calcium (Ca2+) was shown to be its most relevant node. Moreover, considering the present data from our systems biology approach together with the results from the differential gene expression analysis of cerebellar samples from autistic patients, we believe that RAC1, in particular, and the RHO family of GTPases, in general, could play a critical role in the neuropathological events associated with autism. © 2013 Springer Science+Business Media New York.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

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

Bioinformatical and in vitro approaches to essential oil-induced matrix metalloproteinase inhibition

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Construção, caracterização global e local de redes biológicas

A Biologia Sistêmica visa a compreensão da vida através de modelos integrativos que enfatizem as interações entre os diferentes agentes biológicos. O objetivo é buscar por leis universais, não nas partes componentes dos sistemas mas sim nos padrões de interação dos elementos constituintes. As redes complexas biológicas são uma poderosa abstração matemática que permite a representação de grandes volumes de dados e a posterior formulação de hipóteses biológicas. Nesta tese apresentamos as redes biológicas integradas que incluem interações oriundas do metabolismo, interação física de proteínas e regulação. Discutimos sua construção e ferramentas para sua análise global e local. Apresentamos também resultados do uso de ferramentas de aprendizado de máquina que nos permitem compreender a relação entre propriedades topológicas e a essencialidade gênica e a previsão de genes mórbidos e alvos para drogas em humanos

Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Caracterização topológica dos motivos das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

The reducionism method has helped in the clari cation of functioning of many biological process. However, such process are extremely complex and have emergent properties that can not be explained or even predicted by reducionism methods. To overcome these limits, researchers have been used a set of methods known as systems biology, a new area of biology aiming to understand the interactions between the multiple components of biological processes. These interactions can be represented by a mathematical object called graph or network, where the interacting elements are represented by a vertex and the interactions by edges that connect a pair of vertexes. Into graphs it is possible to nd subgraphs, occurring in complex networks at numbers that are signi cantly higher than those in randomized networks, they are de ned as motifs. As motifs in biological networks may represent the structural units of biological processess, their detection is important. Therefore, the aim of this present work was detect, count and classify motifs present in biological integrated networks of bacteria Escherichia coli and yeast Saccharomyces cere- visiae. For this purpose, we implemented codes in MathematicaR and Python environments for detecting, counting and classifying motifs in these networks. The composition and types of motifs detected in these integrated networks indicate that such networks are organized in three main bridged modules composed by motifs in which edges are all the same type. The connecting bridges are composed by motifs in which the types of edges are diferent

Análise ampla do genoma para detecção de erros de montagem no genoma de referência bovino e para detecção de locos relacionados a características de produção e reprodução da raça GIR

Pós-graduação em Genética e Melhoramento Animal - FCAV

Algoritmos de aprendizado semi-supervisionado baseados em grafos aplicados na bioinformática

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

Nanotechnology-based drug delivery systems for treatment of oral cancer: a review

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

Physical attributes of kaolinitic and oxidic oxisols resulting from different usage systems

A mineralogia da fração argila e os sistemas de uso exercem fundamental importância na estrutura do solo. Assim, objetivou-se avaliar atributos físicos de um Latossolo Vermelho Distrófico, caulinítico (LVd), e, de um Latossolo Vermelho Eutroférrico, oxídico (LVef), sob diferentes sistemas de uso, localizados no município de Jaboticabal (SP), Brasil. Os sistemas de uso foram: cana-de-açúcar; algodão e mata. Foram avaliadas a densidade do solo, porosidade total, macro e microporosidade, nas profundidades de 0,0-0,1, 0,1-0,2, 0,2-0,3, 0,3-0,4 m. O Latossolo caulinítico (LVd) apresentou maior densidade do solo e menor porosidade total, macro e microporosidade. O uso aumentou a densidade do solo na profundidade de 0,0-0,3 m, com efeitos maiores no Latossolo caulinítico, principalmente na profundidade de 0,1-0,2 m na área cultivada com cana-de-açúcar.

Polymorphisms of Lewis and Secretor genes are related to breast cancer and metastasis in axillary lymph nodes

ABH and Lewis antigen expression has been associated with cancer development and prognosis, tumor differentiation, and metastasis. Considering that invasive ductal breast carcinoma (IDC) presents multiple molecular alterations, the aim of the present study was to determine whether the polymorphism of ABO, Lewis, and Secretor genes, as well as ABO phenotyping, could be associated with tumor differentiation and lymph nodes metastasis. Seventy-six women with IDC and 78 healthy female blood donors were submitted to ABO phenotyping/genotyping and Lewis and Secretor genotyping. Phenotyping was performed by hemagglutination and genotyping by the polymerase chain reaction with sequence-specific primers. ABO, Lewis, and Secretor genes were classified by individual single nucleotide polymorphism at sites 59, 1067, 202, and 314 of the Lewis gene, 428 of the Secretor gene, and 261 (O1 allele), 526 (O2 and B allele), and 703 (B allele). No association was found between breast cancer and ABO antigen expression (P = 0.9323) or genotype (P = 0.9356). Lewis-negative genotype was associated with IDC (P = 0.0126) but not with anatomoclinical parameters. Nonsecretor genotype was associated with axillary lymph node metastasis (P = 0.0149). In conclusion, Lewis and Secretor genotyping could be useful to predict respectively breast cancer susceptibility and axillary lymph nodes metastasis.

Histopathological and immunohistochemical (cytokeratins AE1/AE3) study of the parametrium of patients with early stage cervical cancer

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)