Frontiers in Bioscience-Landmark (FBL) is published by IMR Press from Volume 26 Issue 5 (2021). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on imrpress.com as a courtesy and upon agreement with Frontiers in Bioscience.
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Academic Editor: Ariel Fernandez
Advancements in high-throughput technology and computational power have brought about significant progress in our understanding of cellular processes, including an increased appreciation of the intricacies of disease. The computational biology community has made strides in characterizing human disease and implementing algorithms that will be used in translational medicine. Despite this progress, most of the identified biomarkers and proposed methodologies have still not achieved the sensitivity and specificity to be effectively used, for example, in population screening against various diseases. Here we review the current progress in computational methodology developed to exploit major high-throughput experimental platforms towards improved understanding of disease, and argue that an integrated model for biomarker discovery, predictive medicine and treatment is likely to be data-driven and personalized. In such an approach, major data collection is yet to be done and comprehensive computational models are yet to be developed.