Pages: pp. 482-483
This special section presents a selection of papers that appeared originally as extended abstracts in the Proceedings of the Seventh Workshop on Algorithms in Bioinformatics (WABI 2007), which took place in Philadelphia on 8-9 September 2007, under the auspices of the International Society for Computational Biology (ISCB), the European Association for Theoretical Computer Science (EATCS), the Penn Genomics Institute, and the Penn Center for Bioinformatics.
The Workshop on Algorithms in Bioinformatics covers research in all aspects of algorithmic work in bioinformatics. The emphasis is on discrete algorithms 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 data sets. The goal is to present recent research results, including significant work-in-progress, and to identify andexplore directions of future research. Specific topics of interest include, but are not limited to:
A major goal of the workshop is to bring together researchers working in a wide spectrum of areas in bioinformatics, ranging from abstract algorithm design to biological data analysis so as to enable a dialogue between application specialists and algorithm designers, mediated by algorithm engineers and high-performance computing specialists. We believe that such a dialogue is necessary for the progress of computational biology, inasmuch as application specialists cannot analyze their data sets without fast and robust algorithms and, conversely, algorithm designers cannot produce useful algorithms without being conversant with the problems faced by biologists.
The eight papers that appear in this special section are the highest ranking among the 133 extended abstracts submitted to the conference. Those contributions, duly expanded, were invited for publication in this special section and they were peer-reviewed according to the procedures that TCBB applies to its standard submissions.
The selected papers offer a vivid snapshot of the spectrum of computational biology problems addressed via algorithmic and machine learning techniques. Some of the contributions report progress in well-recognized areas of computational biology, such as protein structure predic-tion, alignments of sequences, trees, and structures. Others address relatively novel issues related to single nucleotide polymorphism and optimal design of genomic tiling arrays.
Raffaele Giancarlo acknowledges the support of the Italian Ministry of Research, International Italy-Israel Firb Project Pattern Discovery in Discrete Structures with Applications to Bioinformatics and by FIRB Project Bioinformatics for Genomics and Proteomics. Sridhar Hannenhalli acknowledges the support of the US National Institutes of Health.