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DOI: 10.1055/s-0038-1634320
Combining Medical Informatics and Bioinformatics toward Tools for Personalized Medicine
Publication History
Publication Date:
08 February 2018 (online)
Summary
Objectives: Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21st century toward new diagnoses, prognoses, and treatments. Methods: Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology).
Results: Initial predictive models have been developed for a pilot study in Huntington’s disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation.
Conclusions: A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.
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References
- 1 Persidis A. Bioinformatics. Nat Biotech 1999; 17: 828.
- 2 Shortliffe EH. et al. Medical Informatics Computer Applications in Health Care and Biomedicine. 2nd ed. Springer; 2001
- 3 Marcotte EM. The Path Not Taken. Nat Biotech 2002; 19: 626-7.
- 4 Kannel WB. The Framingham Study: historical insight on the impact of cardiovascular risk factors in men vs. women. J Gend Specif Med 2002; 5 (Suppl. 02) 27-37.
- 5 Niland J. Integrating Data and Disciplines: Biostatistics and Biomedical Informatics. Interface 2002, 33rd Symposium on the Interface of Computer Science and Statistics Costa Mesa, Ca.: June 2001
- 6 HSG Huntingon Study Group. www.huntington-study-group.org
- 7 Marder K. et al. Rate of Functional Decline in Huntington’s disease. Neurololgy 2000; 54: 452-8.
- 8 Lucas PJ. et al. Probabilistic and decision theoretic approach to the management of infectious diseases at the ICU. Artif Intell Med 2000; 19 (Suppl. 03) 251-79.
- 9 Malin BA, Sweeney LA. Inferring genotype from clinical phenotype through a knowledge based algorithm. (in process) Pac Symp Biocomput 2002; 41-52.
- 10 Willett WC. Balancing Life-Style and Genomics Research for Disease Prevention. Science 2002; 296 5568 695-8.
- 11 Tanzi RE, Parsons AB. Decoding Darkness, The Search for the Genetic Causes of Alzheimer’s Disease. 2001
- 12 Wingender E. et al. TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res 2000; 28: 316-9.
- 13 Bader GD. et al. BIND – The Biomolecular Interaction Network Database. Nucleic Acids Res 2001; 29 (Suppl. 01) 242-5.
- 14 Pronet Online. www.myriad-pronet.com
- 15 Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 2000; 28: 27-30.
- 16 Xenarios I. et al. DIP: The Database of Interacting Proteins. NAR 2002; 30: 303-5.
- 17 Jenssen TK. et al. A Literature Network of Human Genes for High-Throughput Analysis of Gene Expression. Nature Genetics 2001; 28 (Suppl. 01) 21-8.
- 18 ExPASy Molecular Biology Server / ExPASy – SWISS-PROT and TrEMBL. www.expasy.org/sprot
- 19 Shea MA, Ackers GK. The OR Control Sytem of Bacteriophage Lambda. J Mol Biol 1985; 181: 211-30.
- 20 Arkin A, Ross J, McAdams HH. Stochastic Kinetic Analysis of Developmental Pathway Bifurcation in PhageInfected Escherichia coli Cells. Genetics 1998; 149: 1633-48.
- 21 Endy D, Kong D, Yin J. Intracellular Kinetics of a Growing Virus: A Genetically Structured Simulation for Bacteriophage T7. Biotechnology and Bioengineering 1997; 55 (Suppl. 02) 375-89.
- 22 You L, Suthers PF, Yin J. Effects of Escherichia coli Physiology on Growth of Phage T7 In Vivo and In Silico. J Bacteriology 2002; 184: 1888-94.
- 23 Asthagiri A, Lauffenburger DA. Bioengineering Models of Cell Signaling. Ann Rev Biomed Eng 2000; 31-53.
- 24 Bioinformatics.Org/E-CELL Simulation Environment HQ Page www.bioinformatics.org/e-cell
- 25 The Virtual Cell developed by the NRCAM / Virtual Cell Development. www.nrcam. uchc.edu/vcell_development/vcell_dev.html
- 26 The XML Cover Pages – Home Page / Systems Biology Markup Language (SBML). xml.coverpages.org/sbml.html
- 27 Welcome to cellml.org / CellML.org – What Is CellML?. www.cellml.org/public/about/what_is_cellml.html
- 28 The World Wide Web Consortium / W3C Math Home. www.w3.org/Math
- 29 Edelstein-Keshet L, Spiros A. Exploring the formation of Alzheimer’s Disease senile plaques in Silico. (in press, preprint at www.math.ubc.ca/~a ) J Theor Biol 2001