Pages: pp. 865-866
This special section includes a selection of papers presented at the Sixth International Symposium on Bioinformatics Research and Application (ISBRA), which was held at the University of Connecticut in Storrs on 23-26 May, 2010. The ISBRA symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications. In 2010, 57 papers were submitted in response to the call for papers, out of which 20 papers appeared in the ISBRA proceedings published as volume 6053 of Springer Verlag's Lecture Notes in Bioinformatics series.
A small number of authors were invited to submit extended versions of their symposium papers to this special section. Following a rigorous review process, six papers were selected for publication. The selected papers cover a broad range of bioinformatics topics, including protein structure alignment methods, comparison of biological networks, inference, reconstruction, and analysis of the evolutionary history.
The first paper, “A Spectral Approach to Protein Structure Alignment,” by Yosi Shibberu and Allen Holder gives a novel contact geometry description of protein folds that allows for scaling the distance matrix so that its eigenvalues are positive. This mathematical structure is used to develop two new protein fold alignment algorithms. The first algorithm is fast enough to identify folds in large data sets, while the second additionally incorporates the intrinsic geometry and the 3D geometry of a fold to make high-quality alignments.
In the second paper “Asymmetric Comparison and Querying of Biological Networks,” Nicola Ferraro, Luigi Palopoli, Simona Panni, and Simona E. Rombo propose a novel method for biological network alignment. It exploits differences in the characterization of species—the protein-protein interaction network of a better characterized species guides the alignment to the less characterized one via a finite automaton. The method allows for computing most meaningful protein pairings between networks as well as finding matching subgraphs. Experimental results show that all found matchings are biologically relevant and the technique is robust with respect to the misdefined or misplaced interactions occurred in databases.
The remaining four papers describe new methods in the area of reconstruction of biomolecular evolution. “The Plexus Model for the Inference of Ancestral Multidomain Proteins” by John Wiedenhoeft, Roland Krause, and Oliver Eulenstein introduces a graph-theoretic concept of a novel network-like structure, called plexus, which represents the evolution of protein domains and their combinations. They formulate an optimization problem modeling multidomain protein evolution and describe its solution. The application to empirical data sets results in inferring credible scenarios for the evolution of multidomain proteins and reveals inconsistencies in the initial phylogenetic trees.
“Uncovering Hidden Phylogenetic Consensus in Large Data Sets” by Nicholas D. Pattengale, Andre J. Aberer, Krister M. Swenson, Alexandros Stamatakis, and Bernard M.E. Moret presents a novel framework for defining rogue taxa (i.e., data with no well-defined place in the tree) that maximizes the relative information present in a consensus tree computed upon removing these rogue taxa. This framework leads to a bicriterion optimization problem balancing the loss of taxa with the gain in resolution. A greedy heuristic for finding an appropriate set of rogue data is proposed and tested on pathological cases selected both from the literature as well as from new biological data. Removing rogue data allows to obtain better bootstrap scores for multiple remaining edges. The proposed algorithm can handle large practical data sets.
“Extensions and Improvements to the Chordal Graph Approach to the Multistate Perfect Phylogeny Problem” by Ron Gysel and Dan Gusfield describes an improved chordal graph approach to the classic Multistate Perfect Phylogeny Problem. Triangulations of the partition intersection graph help to formulate integer linear program for finding minimum number characters whose removal will result in perfect phylogeny for the remaining data. This allows, for the first time, the solving of the missing data character removal problem for an arbitrary number of states. A novel speeding-up preprocessing is given for computing of the minimal graph separators also used for solving perfect phylogeny problem with missing data.
“A Consensus Tree Approach for Reconstructing Human Evolutionary History and Detecting Population Substructure” by Ming-Chi Tsai, Guy Blelloch, R. Ravi, and Russell Schwartz deals with the reconstruction of human evolutionary history and detection of population substructure. The proposed method is based on the general consensus tree concept summarizing multiple likely phylogenies on millions of small regions spanning the human genome. Although each of them represent distorted versions of the “global” evolutionary history and population structure, the method can identify major splits or subdivisions between population groups supported by multiple trees. The optimization method based on the minimum description length model assembles a true evolutionary history model resistant to overfitting and to noise in the SNP data and provides a de novo inference of population subgroups comparable in quality to that provided by current best methods.
We would like to thank the program committee members and external reviewers for volunteering their time to review the submissions to the symposium and the special section. We would also like to thank the Editor-in-Chief, Dr. Marie-France Sagot, for continuing to provide us with the opportunity for wider dissemination of the exciting research presented at ISBRA in the IEEE/ACM Transactions on Computational Biology and Bioinformatics. Last, but not least, we would like to thank all ISBRA authors—the symposium could not continue to thrive without their high-quality contributions.
Mark Borodovsky Teresa M. Przytycka Sanguthevar Rajasekaran Alexander Zelikovsky Guest Editors
The work of Teresa M. Przytycka is fully supported by intramural program at the National Library of Medicine, National Institutes of Health.