INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Field-programmable gate array & Control theory. The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Interactogeneous: Disease Gene Prioritization Using Heterogeneous Networks and Full Topology Scores

Abstract: Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease.

Negotiation strategies for autonomous computational agents

Abstract: Autonomous agents operate in complex environments and, over time, conflicts inevitably occur among them. Negotiation is the predominant process for resolving conflicts. This paper presents a generic negotiation model for autonomous agents that handles multiparty, multi-issue and repeated rounds. The model is based on computationally tractable assumptions, accounts for a tight integration of the individual capability of planning and the social capability of negotiation, and formalizes a set of human negotiation procedures.

Using Ontologies for Enterprise Architecture Analysis

Abstract: Enterprise architecture aligns business and information technology through the management of different elements and domains. An architecture description encompasses a wide and heterogeneous spectrum of areas, such as business processes, metrics, application components, people and technological infrastructure. Views express the elements and relationships of one or more domains from the perspective of specific system concerns relevant to one or more of its stakeholders. As a result, each view needs to be expressed in the description language that best suits its concerns. However, enterprise architecture languages tend to advocate a rigid "one-model fits all" approach where an all-encompassing description language describes several architectural domains. This approach hinders extensibility and adds complexity to the overall description language. On the other hand, integrating multiple models raises several challenges at the level of model coherence, consistency and trace ability. Moreover, EA models should be computable so that the effort involved in their analysis is manageable. This work advocates the employment of ontologies and associated techniques in EA for contributing to the solving of the aforementioned issues. Thus, a proposal is made comprising an extensible architecture that consists of a core domain-independent ontology that can be extended through the integration of domain-specific ontologies focusing on specific concerns. The proposal is demonstrated through a real-world evaluation scenario involving the analysis of the models according to the requirements of the scenario stakeholders.