Omics Informatics: From Scattered Individual Software Tools to Integrated Workflow Management Systems
Issue No. 04 - July-Aug. (2017 vol. 14)
Tianle Ma , Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY
Aidong Zhang , Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY
Omic data analyses pose great informatics challenges. As an emerging subfield of bioinformatics, omics informatics focuses on analyzing multi-omic data efficiently and effectively, and is gaining momentum. There are two underlying trends in the expansion of omics informatics landscape: the explosion of scattered individual omics informatics tools with each of which focuses on a specific task in both single- and multi- omic settings, and the fast-evolving integrated software platforms such as workflow management systems that can assemble multiple tools into pipelines and streamline integrative analysis for complicated tasks. In this survey, we give a holistic view of omics informatics, from scattered individual informatics tools to integrated workflow management systems. We not only outline the landscape and challenges of omics informatics, but also sample a number of widely used and cutting-edge algorithms in omics data analysis to give readers a fine-grained view. We survey various workflow management systems (WMSs), classify them into three levels of WMSs from simple software toolkits to integrated multi-omic analytical platforms, and point out the emerging needs for developing intelligent workflow management systems. We also discuss the challenges, strategies and some existing work in systematic evaluation of omics informatics tools. We conclude by providing future perspectives of emerging fields and new frontiers in omics informatics.
Bioinformatics, Genomics, Sequential analysis, Informatics, Proteins, RNA, DNA
T. Ma and A. Zhang, "Omics Informatics: From Scattered Individual Software Tools to Integrated Workflow Management Systems," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 14, no. 4, pp. 926-946, 2017.