Incorporating partial matches within multiobjective pharmacophore identification

Incorporating partial matches within multiobjective pharmacophore identification

This paper describes the extension of our earlier multi-objective method for generating plausible pharmacophore hypotheses to incorporate partial matches. Diverse sets of molecules rarely adopt exactly the same binding mode, and so allowing the identification of partial matches allows our program to be applied to larger and more diverse datasets. The method explores the conformational space of ...

Partial Matches and theInterpretation of

Generation of multiple pharmacophore hypotheses using multiobjective optimisation techniques

Pharmacophore methods provide a way of establishing a structure activity relationship for a series of known active ligands. Often, there are several plausible hypotheses that could explain the same set of ligands and, in such cases, it is important that the chemist is presented with alternatives that can be tested with different synthetic compounds. Existing pharmacophore methods involve either...

PMPM: Prediction by Combining Multiple Partial Matches

The prediction by partial matching (PPM) algorithm has been well known for its high prediction accuracy. Recent proposals of PPM-like predictors confirm its effectiveness on branch prediction. In this paper, we introduce a new branch prediction algorithm, named Prediction by combining Multiple Partial Matches (PMPM). The PMPM algorithm selectively combines multiple matches instead of using the ...

Scalable Web Service Composition with Partial Matches

We will investigate scalable algorithms for automated Semantic Web Service Composition (WSC). Our notion of WSC is very general: it allows the generation of new constants by Web service outputs; the composition semantics includes powerful background ontologies; and we use the most general notion of matching, partial matches, where several services can cooperate each covering only a part of a re...