Simón Bolívar University

About: Simón Bolívar University is a education organization based out in Caracas, Venezuela. It is known for research contribution in the topics: Population & Crystallization. The organization has 5912 authors who have published 8294 publications receiving 126152 citations.

Another look at the degree-Kirchhoff index

Abstract: Let G be an arbitrary graph with vertex set {1,2, …,N} and degrees di ≤ D, for fixed D and all i, then for the index R′(G) = ∑i < jdidjRij we show that We also show that the minimum of R′(G) over all N-vertex graphs is attained for the star graph and its value is 2N2 − 5N + 3. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011

Drug-Target Interaction Prediction Using Semantic Similarity and Edge Partitioning

Abstract: The ability to integrate a wealth of human-curated knowledge from scientific datasets and ontologies can benefit drug-target interaction prediction. The hypothesis is that similar drugs interact with the same targets, and similar targets interact with the same drugs. The similarities between drugs reflect a chemical semantic space, while similarities between targets reflect a genomic semantic space. In this paper, we present a novel method that combines a data mining framework for link prediction, semantic knowledge (similarities) from ontologies or semantic spaces, and an algorithmic approach to partition the edges of a heterogeneous graph that includes drug-target interaction edges, and drug-drug and target-target similarity edges. Our semantics based edge partitioning approach, semEP, has the advantages of edge based community detection which allows a node to participate in more than one cluster or community. The semEP problem is to create a minimal partitioning of the edges such that the cluster density of each subset of edges is maximal. We use semantic knowledge (similarities) to specify edge constraints, i.e., specific drug-target interaction edges that should not participate in the same cluster. Using a well-known dataset of drug-target interactions, we demonstrate the benefits of using semEP predictions to improve the performance of a range of state-of-the-art machine learning based prediction methods. Validation of the novel best predicted interactions of semEP against the STITCH interaction resource reflect both accurate and diverse predictions.

An admissible heuristic for SAS+ planning obtained from the state equation

Abstract: Domain-independent optimal planning has seen important breakthroughs in recent years with the development of tractable and informative admissible heuristics, suitable for planners based on forward state-space search. These heuristics allow planners to optimally solve an important number of benchmark problems, including problems that are quite involved and difficult for the layman. In this paper we present a new admissible heuristic that is obtained from the state equation associated to the Petri-net representation of the planning problem. The new heuristic, that does not fall into one of the four standard classes, can be computed in polynomial time and is competitive with the current state of the art for optimal planning, as empirically demonstrated over a large number of problems, mainly because it often shows an improved quality-to-cost ratio. The new heuristic applies to SAS+ planning tasks with arbitrary non-negative action costs.

Results from the Antarctic Muon and Neutrino Detector Array

Abstract: We show new results from both the older and newer incarnations of AMANDA (AMANDA-B10 and AMANDA-II, respectively). These results demonstrate that AMANDA is a functioning, multipurpose detector with significant physics and astrophysics reach. They include a new higher-statistics measurement of the atmospheric muon neutrino flux and preliminary results from searches for a variety of sources of ultrahigh energy neutrinos: generic point sources, gamma-ray bursters and diffuse sources producing muons in the detector, and diffuse sources producing electromagnetic or hadronic showers in or near the detector.