Bioinformatics and Genomic Medicine.
- Author:
Ju Han KIM
1
Author Information
1. Department of Preventive Medicine, Seoul National University College of Medicine, Korea.
- Publication Type:Original Article
- Keywords:
Bioinformatics;
Genomics;
Proteomics;
Medical informatics;
Microarray
- MeSH:
Machine Learning;
Biochemistry;
Computational Biology*;
Data Mining;
Genomics;
Genotype;
Informatics;
Information Systems;
Medical Informatics;
Phenotype;
Proteomics
- From:Korean Journal of Preventive Medicine
2002;35(2):83-91
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolutions both in bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics.Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. The paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization, primary pattern analysis, and machine learning algorithms will be presented. Use of integrated biochip informatics technologies, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.
