Introduction to Mini-Track: Advanced Computational Approaches and IT Techniques in Bioinformatics

The last few years have witnessed significant developments in the area of Bioinformatics. With more researchers taking on Bioinformatics projects that integrate theoretical and applied concepts from both the Computational Sciences as well as the Bioscience, the discipline of Bioinformatics is quickly emerging as an exciting independent field of research. As a result, new educational and research programs have been developed, new scientific journals have been launched and various professional conferences have been dedicating sessions or mini-tracks to disseminate current Bioinformatics research. With the diversity and multidisciplinary nature of HICSS, having a Bioinformatics focused mini-track appears to be very fitting. With the growing number of computer science researchers and IT specialists in Bioinformatics, the mini-track provides an excellent dissemination vehicle for their research activities. In addition, the mini-rack allows Biosciences researchers to have an in-depth view of Bioinformatics in mathematical, computational and IT perspectives. The focus of the Bioinformatics mini-track is on addressing advanced computational and IT tools in Bioinformatics. The first three papers in the mini-track focus on the development of IT for Bioinformatics, while the last two papers present advanced computational approaches for data mining and motif finding in Biological databases. The first paper of the mini-track, “MicroMultitest: Ranking Differentially-Expressed Genes in Microarray Data,” by Xiao et al. presents a microarray data analysis toolkit, called MicroMultitest. Several statistical tests, such as t-test, adapted SAM and adjusted p-value methods and ROC curve technique are implemented in MicroMultitest. This toolkit allows one to automatically find a list of genes that have significant level of expressions and to improve accuracy of ranking differentially-expressed genes in DNA Microarray data. The second paper, “Data Management and Analysis Architecture for a More Efficient and Productive Bioinformatics Environment,” by Ang addresses the main challenge facing Bioinformatics researchers, particularly those focusing on the Bioscience aspect of Bioinformatics. The challenge is how to take advantage of the current available IT Bioinformatics tools without extensive background in Computational Sciences. The paper proposes a flexible architecture that provides valuable data and computation resources in a way that does not demand IT background. The third paper, “Bioinformatics Approach for Exploring MS/MS Proteomics Data,” by Singhal et al. presents another IT tool that provides an environment for the specific domain of Mass Spectrometry (MS). The paper describes a computational environment for system biology that provides an integrated access to heterogonous databases and analysis applications for exploring MS proteomics data. The last two papers of the mini-track focus on developing advanced algorithms and computational tools for mining biological data. The forth paper, “A New Scheme for Protein Sequence Motif Extraction,” by Yang et al presents a Suffix Tree Model to model protein sequences and extract specific motifs while allowing mismatches and gaps. In the final paper of the mini-track, “A Grammer Based Approach for Mining Bioinformatics Databases,” by Quest et al., a new formal approach for mining biological data sets is presented. The proposed grammar based approach provides a flexible and powerful tool for advanced sequence comparison and data mining. The formal grammar and its corresponding data mining engine is capable of extracting records from biological databases, filtering a subset of those records for mining, and sorting the obtained records based on similarity scheme designed by the user. In summary, the papers of the Bioinformatics Minitrack, while focusing on IT tools for addressing Bioinformatics needs, provide a diverse spectrum of innovative ways to integrate Computational and Biological. Hence, they provide further attempts to establish the area of Bioinformatics as a new and exciting scientific discipline.