KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
Computational Bioscience Research Center (CBRC)
Online Publication Date2018-12-13
Print Publication Date2018-11-01
Permanent link to this recordhttp://hdl.handle.net/10754/630287
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AbstractThe papers in this special section were presented at the 16th International Workshop on Data Mining in Bioinformatics (BIOKDD17). The BIOKDD17 Workshop was organized in conjunction with the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining on August 14, 2017 in Halifax, Canada. It brought together international researchers in the interacting disciplines of data mining, medical informatics, and bioinformatics at the World Trade and Convention Centre venue. The goal of this workshop is to encourage Knowledge Discovery and Data mining (KDD) researchers to take on the numerous challenges that bioinformatics offers. Bioinformatics is the science of managing, mining, and interpreting information from biological data. Various genome projects have contributed to an exponential growth in DNA and protein sequence databases. Rapid advances in high-throughput technologies, such as microarrays, mass spectrometry, and new/next-generation sequencing, can monitor quantitatively the presence or activity of thousands of genes, RNAs, proteins, metabolites, and compounds in a given biological state. The ongoing influx of these data, the pressing need to address complex biomedical challenges, and the gap between the two have collectively created exciting opportunities for data mining researchers.
CitationGao X, Chen JY, Zaki MJ (2018) Multiscale and Multimodal Analysis for Computational Biology. IEEE/ACM Transactions on Computational Biology and Bioinformatics 15: 1951–1952. Available: http://dx.doi.org/10.1109/tcbb.2018.2838658.