Mounting amounts of diverse biomedical data have been generated. Extracting meaningful information from these datasets has relied on the efforts of informaticians, who are extensively trained in the computer science realm, with little to no training in biology. Similarly, biologists in general are not proficient to analyze, annotate, and translate their large datasets into valuable biomedical insights. In addition, there has been an overall lack of public understanding for the importance of Big Data science, hindering the enthusiasm to advance data science in the biomedical field. To bridge the gaps that exist among data generation, interpretation and awareness, our training program will provide critical data science education to current biomedical researchers, expand the data science workforce in the biomedical field, and elicit a broad public recognition of data science. Accordingly, we have engineered an integrated training program with four specific aims: 1) To empower current biomedical researchers with the ability to manage and interpret Big Data by gaining proficiency in utilizing data science software tools;2) To utilize the training component as an interactive testing field for software packages developed by the Data Science Research (DSR) component. User critiques/feedback will refine and transform software tools to a professional grade, facilitating the community to capture the full value of Big Data;3) To cultivate a new generation of developers with transdisciplinary expertise in both computational biology and biomedical informatics;and 4) To heighten public awareness of and enthusiasm for the substantial opportunities embedded within computational biology, which has the potential to transform biomedical research and medicine. To achieve these aims, we have constructed three trainee-oriented modules: Biomedical Researcher /User-Oriented Module, Big Data Science Researcher-Oriented Module, and General Public-Oriented Module. A trans-institutional collaboration has been organized (i.e., UCLA, TSRI, UMMC, and EMBL-EBI), and all components have demonstrated outstanding track records in education. This collaboration will ensure successful execution of the training component substantiated by distinguished experts and meritorious educators from a wide breadth of disciplines, spanning -omics, bioinformatics, and computational science.
The challenges of biomedical Big Data are multifaceted. Advances in biomedical sciences using Big Data will require an adequate workforce with the appropriate data science expertise and skills, including those in computational biology, biomedical informatics, and related areas. Users of Big Data software tools and resources must be trained to use them well. This Training Component is designed to address these challenges.
|Torkamani, Ali; Andersen, Kristian G; Steinhubl, Steven R et al. (2017) High-Definition Medicine. Cell 170:828-843|
|DeLeon-Pennell, Kristine Y; Iyer, Rugmani Padmanabhan; Ero, Osasere K et al. (2017) Periodontal-induced chronic inflammation triggers macrophage secretion of Ccl12 to inhibit fibroblast-mediated cardiac wound healing. JCI Insight 2:|
|Tontonoz, Peter; Wu, Xiaohui; Jones, Marius et al. (2017) Long Noncoding RNA Facilitated Gene Therapy Reduces Atherosclerosis in a Murine Model of Familial Hypercholesterolemia. Circulation 136:776-778|
|Wang, Jie; Lee, Jessica; Liem, David et al. (2017) HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum. Gene 618:14-23|
|Jones, Marilyn C; Topol, Sarah E; Rueda, Manuel et al. (2017) Mutation of WIF1: a potential novel cause of a Nail-Patella-like disorder. Genet Med 19:1179-1183|
|Garlid, Anders Olav; Polson, Jennifer S; Garlid, Keith D et al. (2017) Equipping Physiologists with an Informatics Tool Chest: Toward an Integerated Mitochondrial Phenome. Handb Exp Pharmacol 240:377-401|
|Nielsen, Signe Holm; Mouton, Alan J; DeLeon-Pennell, Kristine Y et al. (2017) Understanding cardiac extracellular matrix remodeling to develop biomarkers of myocardial infarction outcomes. Matrix Biol :|
|Rueda, Manuel; Torkamani, Ali (2017) SG-ADVISER mtDNA: a web server for mitochondrial DNA annotation with data from 200 samples of a healthy aging cohort. BMC Bioinformatics 18:373|
|Meschiari, Cesar A; Ero, Osasere Kelvin; Pan, Haihui et al. (2017) The impact of aging on cardiac extracellular matrix. Geroscience 39:7-18|
|Jung, Mira; Ma, Yonggang; Iyer, Rugmani Padmanabhan et al. (2017) IL-10 improves cardiac remodeling after myocardial infarction by stimulating M2 macrophage polarization and fibroblast activation. Basic Res Cardiol 112:33|
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