Disruptive Strategies for Removing Drug Discovery Bottlenecks

Flexible Text Mining Strategies for Drug Discovery

The two text mining strategies: finding co-occurrences of biological entities within documents, and finding relationships using Natural Language Processing, are often seen as competitors. Here we adopt a flexible approach where the techniques are adapted and combined to suit the nature of the document corpus, and the specific task. The approach was tested on three tasks relevant to cancer treat...

Ethnobotany, Ethnopharmacology and Drug Discovery

     This manuscript is a review of a number of ethnobotany and ethnopharmacology texts and papers in order to arrive at current understanding and scope of ethnobotany and ethnopharmacology. It includes either a brief definition of both fields and presenting some examples on them. Also it has a glimpse on the geographical coverage of research works throughout the world, important issue of prope...

Computational Strategies in Cancer Drug Discovery

Finding and Removing Performance Bottlenecks in Large Systems

Software systems obey the 80/20 rule: aggressively optimizing a vital few execution paths yields large speedups. However, finding the vital few paths can be difficult, especially for large systems like web applications. This paper describes a novel approach to finding bottlenecks in such systems, given (possibly very large) profiles of system executions. In the approach, for each kind of profil...

Current Advances in Computational Strategies for Drug Discovery in Leishmaniasis

Andrés F. Flórez1,2, Stanley Watowich3 and Carlos Muskus2 1German Cancer Research Center (DKFZ)/ Division Theoretical Systems Biology, Heidelberg 2Universidad de Antioquia/Programa de Estudio y Control de Enfermedades Tropicales – PECET, Medellín 3University of Texas Medical Branch/Department of Biochemistry and Molecular Biology and the Sealy Center for Structural Biology and Molecular Biophys...