In recent years, especially after the completion of genome sequencing projects for various organisms, there has been a growing interest in the study of regulation and gene expression mechanisms. The amount of data available makes it unfeasible to pursue a manual analysis calling for some sort of automatic processing. In this context, bioinformatics tools have become more and more central to the activity of biologists.

Recent developments in DNA chips now enable the simultaneous measure of the expression level of a large number of genes (sometimes all the genes of an organism) for a given experimental condition. Most commonly, gene expression data is arranged in a data matrix, where each gene corresponds to one row and each condition to one column. The conditions may correspond to different time points, different environmental conditions, different organs or different individuals. Simply visualizing this kind of data is challenging. Using it to extract biologically relevant knowledge is even harder.

Approximate string matching is the problem of finding a pattern in a text allowing for some errors to occur.

This talk will address recent developments in grammatical inference, with emphasis on the ADIOS approach (Automatic DIstillation Of Structure), a system for the inference of natural language grammars that has been shown to perform well in language proficiency tests. The methods achieves this remarkable result by using better statistical techniques for distinguishing constituents from non-constituents.

A major problem within peer-to-peer systems is to find the best peer given a certain query. Inspired by the work in the area of social networks we present a novel peer-to-peer system called INGA (Interest-based Node Grouping Architecture). Peers cooperate to efficiently route queries along adaptive shortcuts based overlays using only local knowledge. We propose active and passive shortcut creation strategies and a new routing algorithm that combines a greedy, high degree and flooding based search depending on one's knowledge.

Apesar do sucesso da pesquisa de informação na "Internet" baseada em palavras chave, uma parte significativa das tarefas de pesquisa requer informação semântica sobre os dados. Propõe-se uma abordagem que combina uma pequena ontologia, construída manualmente, com um método de associação automática dos conceitos a partes de artigos técnicos disponíveis na "Web". Esta abordagem, combinada com uma linguagem de procura especializada, permite realizar pesquisas avançadas que não são possíveis usando as ferramentas actuais.

Entre as muitas novas técnicas de Recuperação de Informação (RI) criadas no contexto da Web, análise de ligações é uma que tem atraído grande atenção. Neste trabalho, estudamos como ligações entre páginas Web podem ser aplicadas na resolução de dois problemas distintos: (a) ordenação de respostas a uma consulta e (b) classificação de documentos da Web. Para isso, modelos formais baseados em redes Bayesianas são propostos e validados através de testes executados numa colecção extraída da Web brasileira.

Algoritmos de pesquisa por caminhos são estudados desde a antiguidade, mas desenvolveram-se formalmente sobre o modelo de matemático de Grafo principalmente no século passado. O algoritmo de Dijkstra apresentado em 1959 faz uma pesquisa BFS à partir da origem até encontrar o destino. Em 1968 Hart, Nilsson e Raphael apresentaram o algoritmo A*, que usa informações da estrutura do grafo para saber quais são os nodos mais promissores a pesquisar. A* inaugurou a "pesquisa heurística", mas ainda assim é capaz de encontrar o caminho ótimo.

This seminar will discuss the application of text mining to automate the identification of the function of large sets of genes from the biomedical literature. An approach will be presented to obtain this knowledge as annotations that associate biologic entities to Gene Ontology terms.

The conformational energy of a molecule in solution consists of two components: the intramolecular potential energy of the molecule and the solvation free energy of the molecule, the latter describing its interaction with the solvent. Although the intramolecular potential energy of small organic molecules can be calculated to a high degree of accuracy with modern Quantum Mechanical methods, biological macromolecules such as proteins and nucleic acids are far too large for the application of these methods.