Translational bioinformatics

Biomedical Informatics: Computer Applications in Health Care and Biomedicine: Fourth Edition

Volumn , Issue , 2014, Pages 721-754

  Tenenbaum, Jessica D ^a   Shah, Nigam H ^b   Altman, Russ B ^c  

^a DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERS;

COMPUTER SCIENCE;

EID: 84925665201     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-4471-4474-8_25     Document Type: Chapter

References (10)

1. Altman, R. B., & Miller, K. S. (2011). 2010 translational bioinformatics year in review. Journal of the American Medical Informatics Association, 18, 358-366. This article summarizes Dr. Altman's third annual "year in review" presentation delivered at the 2010 AMIA Joint Summits on Translational Science in San Francisco.
2. Angrist, M. (2010). Here is a human being: at the dawn of personal genomics. New York: Harper. This text is written by one of the Personal Genome Project's first subjects, describing the project, the cohort, and the experience. It also gives a good overview of the background of the project and a number of ethical, legal, and social issues that it raises.
3. Capriotti, E., Nehrt, N. L., Kann, M. G., & Bromberg, Y. (2012 July). Bioinformatics for personal genome interpretation. Briefings in Bioinformatics, 13 (4), 495-512. The authors of this review summarize key databases and bioinformatics tools that have been developed in recent years to aid in the intepretation of genomic variance. Resources covered include databases of variants, genotype/phenotype annotation databases, tools for gene prioritization and tools for interpretation of single nucleotide variants.
4. Davies, K. (2010). The $1000 genome: The revolution in DNA sequencing and the new era of personalized medicine. New York: Free Press. This text, written by the editor of BioIT World magazine, documents the characters, events, and issues in the race to achieve the $1000 Genome.
5. Hastie, T., Tibshirani, R., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction. New York: Springer. A useful primer on the statistical concepts underlying machine learning approaches to biomarker discovery.
6. Kann, M.G., & Lewitter, F., (Eds.). (2012). Translational bioinformatics. PLOS Computational Biology Collections eBook. This eBook represents both the first "textbook" devoted entirely to TBI, and the first online, open access textbook from PLOS. In addition to many of the topics covered in this chapter, the collection includes chapters on related topics such as cancer genome analysis, micribiome analysis, structural variation, and protein interactions in disease.
7. Masys, D. R., Jarvik, G. P., Abernethy, N. F., Anderson, N. R., Papanicolaou, G. J., Paltoo, D. N., Hoffman, M. A., Kohane, I. S., & Levy, H. P. (2012). Technical desiderata for the integration of genomic data into electronic health records. Journal of Biomedical Informatics, 45 (3), 419-422. The authors describe the characteristics of biomolecular data that differentiate it from other EHR data, enumerate a set of technical desiderata for management of biomolecular data in clinical settings (e.g., separation of molecular data observations from clinical interpretation, lossless data compression, support for readability by both humans and machines), and propose a technical approach to its representation.
8. Payne P.R.O., Sarkar, I.N., Embi, P.J., & Kahn M. (2011, December). Journal of Biomedical Informatics, 44 (Suppl 1), S1-S108. This supplement to JBI's 44th volume highlights the top papers from the 2011 AMIA Joint Summits on Translational Science. An editorial by N. Sarkar, 2011 TBI scientific program committee chair, gives an overview of the conference contents, and provides context for the papers selected to appear in this issue.
9. Sarkar, I. N., & Payne, P. R. O. (2011, December). The joint summits on translational science: crossing the translational chasm. Journal of Biomedical Informatics, 44 (Suppl 1), S1-2. This editorial discusses the spectrum of biomedical informatics, from biology to medicine, in the context of the NIH Roadmap and the Clinical and Translational Science Award program. It gives the history of the AMIA Joint Summits on Translational Science, and explains the emergence of TBI and CRI as disciplines unto themselves, intended to address the same issues that motivated those initiatives-namely translating scientific discoveries into meaningful changes in health care delivery.
10. Sarkar, I. N., Butte, A. J., Lussier, Y. A., Tarczy-Hornoch, P., & Ohno-Machado, L. (2011). Translational bioinformatics: linking knowledge across biological and clinical realms. Journal of the American Medical Informatics Association, 18, 354-357. The authors present the field of TBI in the context of successes from bioinformatics and health informatics.