eTRIKS IT platfroms for large-scale biomedical research

Pandis, Ioannis; Guo, Yike; Guitton, Florian; Yang, Xian; Sun, Kai; Wang, S.; Jullian, N.; Bansal, Aasthaa; Corfield, Julie; Pavlidis, Stelios; Hekking, Pieter Paul; Fleming, Louise; Shaw, Daniel S.; Roberts, Graham; Fitch, Naomi; Riley, John; Wagers, Scott; Rowe, Anita; Adcock, Ian M.; Chung, Kian Fan; Auffray, Charles; Sterk, Peter J.

doi:10.1183/13993003.congress-2015.pa3976

Cited by 2 publications

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“…These advantages can support multiparty consortia, such as OncoTrack, which involves a body of investigators from different backgrounds working in cooperation on the datasets created inside the project. In the eTRIKS consortium, the platform was expanded to combine progressive, user-friendly, and transferable functions 143,[145][146][147][148] The Oracle Health Sciences Translational Research Center (TRC) supplies a standardized industrial platform that can store, combine, and analyze multiomics and clinical data; it is particularly suitable for analyzing biomarkers and providing confirmation for use in clinical trials. 115…”

Section: Data Platforms For Translational Medicine and Integration Of Multiomicsmentioning

confidence: 99%

Section: Data Platforms For Translational Medicine and Integration Of Multiomicsmentioning

confidence: 99%

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Approaches for the integration of big data in translational medicine: single‐cell and computational methods

Amirmahani

Ebrahimi

Molaei

et al. 2021

Annals of the New York Academy of Sciences

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Translational medicine describes a bench-to-bedside approach that eventually converts findings from basic scientific studies into real-world clinical research. It encompasses new treatments, advanced equipment, medical procedures, preventive and diagnostic approaches creating a bridge between basic studies and clinical research. Despite considerable investment in basic science, improvements in technology, and increased knowledge of the biology of human disease, translation of laboratory findings into substantial therapeutic progress has been slower than expected, and the return on investment has been limited in terms of clinical efficacy. In this review, we provide a fresh perspective on some experimental and computational approaches for translational medicine. We cover the analysis, visualization, and modeling of high-dimensional data, with a focus on single-cell technologies, sequence, and structure analysis. Current challenges, limitations, and future directions, with examples from cancer and fibrotic disease, will be discussed.

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