GoingToMeet

All research on algorithmic work in bioinformatics and systems biology. The emphasis is on discrete algorithms and machine-learning methods that address important problems in molecular biology, that are founded on sound models, that are computationally efficient, and that have been implemented and tested in simulations and on real datasets. The goal is to present recent research results, including significant work-in-progress, and to identify and explore directions of future research.

The Workshop on Algorithms in Bioinformatics (WABI) is sponsored by EATCS (the European Association for Theoretical Computer Science) and ISCB (the International Society for Computational Biology).

Topics:
Original research papers (including significant work-in-progress) are solicited in all aspects of algorithms in bioinformatics, including, but not limited to:

• Exact, approximate, and machine-learning algorithms for sequence analysis, gene and signal recognition, alignment and assembly, molecular evolution, structure determination or prediction, gene expression, pathways, gene networks, proteomics, functional genomics, and drug design.
• High-performance computing approaches to computationally hard learning and optimization problems in bioinformatics.
• Methods, software and dataset repositories for development and testing of such algorithms and their underlying models.