Translational bioinformatics is an emerging field that aims to exploit various kinds of biological data for useful knowledge to be translated into clinical practice. However, the flooding of the huge amount of omics data makes it a big challenge to analysis and to interpret these data.

Therefore, it is highly demanded to develop new efficient computational methodologies, especially data mining approaches, for translational bioinformatics. This special issue aims to bridge the data mining and translational bioinformatics and provide the recent progress in data mining technologies as well as their applications to translational bioinformatics. Potential topics include, but are not limited to:

• Biomarker discovery
• Disease gene prediction
• Drug discovery
• Drug-protein interaction
• Drug-drug interaction
• Drug toxicity/side effect
• Text mining for translational bioinformatics
• Identification of genomic variations
• Bioimage informatics
• Computational methodologies in translational bioinformatics

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/bmri/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/bmri/computational.biology/datam/ according to the following timetable: