CSLPB · Constraint solving and language processing for bioinformatics

Final Activity Report Summary - CSLPB (Constraint Solving and Language Processing for Bioinformatics)

Unprecedented volume growth of biological data over the past few years has created formidable challenges to the fields of computational molecular biology and of biological knowledge retrieval. Previous information processing methods cannot keep up with this "information tsunami", which washes over heterogeneous landscapes, most notably: human language text produced in the form of articles, books, web sites, etc. and genetic code text in nucleic acid language, such as DNA sequences. Meaningful, useful, and in particular, timely processing of these sources needs to conjure the full power of all we have learnt so far in the fields of natural language processing, text mining and logical inference. This project developed theories, tools and applications in the intersection of these three fields, in the expectation that the present formidable challenges may be turned into formidable opportunities for scientific breakthrough, by synergistically exploiting the state-of-the-art that each of these fields has arrived at independently. We achieved a fertile integration between Biology and AI, which most notably yielded a biologically inspired model for computational linguistics (Best Paper Award, IWINAC 09 [11]), and a most useful methodology for DNA bar-code discovery. It has also had enormous scientific impact in practical terms e.g. our resulting software for plant pathology identification from signature oligos reduced what used to be a six month-person effort to an average of 20 minutes of computing and is now used daily by Agriculture and Agri-Food Canada. We developed high level reasoning methodologies, using and extending Constraint Handling Rules, and resulting in new programming capabilities: Abductive Logic Grammars, capable of constructing knowledge bases as a parse by product and Biological Formation Concept Formation Concept Grammars, capable of forming new concepts from others found in heterogeneous sources about biology. In recognition to these ground-breaking contributions to Constraint Handling Rules, my name has been included in the Constraint Handling Rules Hall of Fame.

Data: CORDIS, © European Union