The problem of choosing from a set of projects which ones should be executed and whenthey should start, depending on several restrictions involving project costs, risks, limited resources, dependencies among projects, and aiming at different, even conflicting, goals is known as the project portfolio selection (PPS) problem. We study a particular version of the PPS problem stemming from the operation of a real power generation company. It includes distinct categories of resources, intricate dependencies between projects, which are especially important for the management of power plants, and the prevention of risks. We present an algorithm based on the GRASP meta-heuristic for finding better results thanmanual solutions produced by specialists. The algorithm yielded solutions that decreased the risk by 47%, as measured by the company's standard methodology.

O projeto SUCEST (Sugarcane EST Project) produziu 291.904 ESTs de cana-de-açúcar. Nesse projeto, o Laboratório de Bioinformática criou o web site que foi o "ponto de encontro" dos 74 laboratórios de sequenciamento e data mining que fizeram parte do consórcio para o projeto. O Laboratório de Bioinformática (LBI) recebeu, processou, analisou e disponibilizou ferramentas para a exploração dos dados. Neste artigo os dados, serviços e programas implementados pelo LBI para o projeto são descritos, incluindo o procedimento de clustering que gerou 43.141 clusters.

The Sugarcane EST project (SUCEST) produced 291,904 expressed sequence tags (ESTs) in a consortium that involved 74 sequencing and data mining laboratories. We created a web site for this project that served as a ‘meeting point’ for receiving, processing, analyzing, and providing services to help explore the sequence data. In this paper we describe the information pathway that we implemented to support this project and a brief explanation of the clustering procedure, which resulted in 43,141 clusters.

In this text we attempt to unify many results about the K operator based on a new theory involving graphs, families and operators. We are able to build an ''operator algebra'' that helps to unify and automate arguments. In addition, we relate well-known properties, such as the Helly property, to the families and the operators. As a result, we deduce many classic results in clique graph theory from the basic fact that CS = I for conformal, reduced families. This includes Hamelink's construction, Roberts and Spencer theorem, and Ban-delt and Prisner's partial characterization of clique-fixed classes [2]. Furthermore, we show the power of our approach proving general results that lead to polynomial recognition of certain graph classes.