OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Analyzing the effect of homogeneous frustration in protein folding

The energy landscape theory has been an invaluable theoretical framework in the understanding of biological processes such as protein folding, oligomerization, and functional transitions. According to the theory, the energy landscape of protein folding is funneled toward the native state, a conformational state that is consistent with the principle of minimal frustration. It has been accepted that real proteins are selected through natural evolution, satisfying the minimum frustration criterion. However, there is evidence that a low degree of frustration accelerates folding. We examined the interplay between topological and energetic protein frustration. We employed a Cα structure-based model for simulations with a controlled nonspecific energetic frustration added to the potential energy function. Thermodynamics and kinetics of a group of 19 proteins are completely characterized as a function of increasing level of energetic frustration. We observed two well-separated groups of proteins: one group where a little frustration enhances folding rates to an optimal value and another where any energetic frustration slows down folding. Protein energetic frustration regimes and their mechanisms are explained by the role of non-native contact interactions in different folding scenarios. These findings strongly correlate with the protein free-energy folding barrier and the absolute contact order parameters. These computational results are corroborated by principal component analysis and partial least square techniques. One simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins. © 2013 Wiley Periodicals, Inc.

Modelagem molecular da Chiquimato quinase de Mycobacterium leprae

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem molecular da interação entre a proteína de fusão do vírus sincicial respiratório humano e inibidores da ação viral. -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização molecular e expressão heteróloga do alérgeno fosfolipase A1 do veneno de Polybia paulista (Hymenoptera; Vespidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise comparativa da expressão protéica em glândulas pós-faríngeas de saúva-limão, Atta sexdens rubropilosa Forel, 1908 (Hymenoptera: Formicidae) submetidas à suplementação lipídica

Pós-graduação em Ciências Biológicas (Biologia Celular e Molecular) - IBRC

Identificação de fatores de transcrição de Neurospora crassa envolvidos na regulação do metabolismo de glicogênio

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Paralelização da ferramenta de alinhamento de sequências MUSCLE para um ambiente distribuído

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

Algoritmos de alinhamento múltiplo e técnicas de otimização para esses algoritmos utilizando Ant Colony

Pós-graduação em Ciência da Computação - IBILCE

Purificação, caracterização, cristalização e modelagem molecular teórica da fração giroxina do veneno de Crotalus durissus terrificus (Laurenti 1768)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação e caracterização de possiveis marcadores moleculares em carcinoma renal de células claras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Identificação de estirpes de rizóbios por seqüenciamento parcial dos genes 16S rDNA e nifH

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise por ferramentas de bioinformática da proteína não-estrutural 5A do vírus da hepatite C genótipo 1 e 3 em amostras pré-tratamento

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de Pipelines para análise de EST, bibliotecas ITS e 16S para estudos genômicos em formigas Attini

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