NDLI: Bioinformatics databases and applications: a challenging landscape

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Bioinformatics databases and applications: a challenging landscape

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Bioinformatics databases and applications: a challenging landscape

Content Provider	ACM Digital Library
Author	Navathe, Shamkant B.
Abstract	The biological science studies the phenomenon of life and encompasses an enormous variety of information. After the sequencing of the entire human genome, the field of genomics and proteomics has indeed come into limelight. The objective of Genomics is to undertake a systematic investigation of genomes while Proteomics deals with the quantitative measurement of protein expression. Data management of such highly variable complex biological phenomena now poses a challenge for database technology and includes data that ranges from research articles to complex metabolic pathways. Research advances in computational biology, molecular biology, genomic medicine and pharmacogenomics have now become critically dependent on what information such databases contain. It is not possible with the available technology of web links to get a complete and uniform picture of where science stands today on any one of these organisms unless a scientist spends many hours using search engines with some associated frustration. Metadata management, data interpretation, data integration, uniform interface creation, and visualization pose challenges with major opportunities for database research.In this talk, the speaker will review a number of essential biological concepts required to understand this complex field. We will then survey the proliferation of genomic and proteomic databases around the world and describe the unique characteristics of biological data that make their management difficult. We highlight the pressing issues for further development of these databases and related applications where database research and development may contribute substantially.We will give illustrations from our ongoing work in the area of development of a mitochondrial genome database, text mining of Medline to discover functional relationships among genes, classification of literature to extract epidemiologically relevant articles, and integration of protein, microarray and protein data for ovarian cancer patients. There is a shift in emphasis from data accumulation to data analysis, interpretation and understanding in biological, studies that is likely to expand. Further database research will go a long way to contribute to many public and private efforts in the broadly defined field of bioinformatics.
Starting Page	1
Ending Page	2
Page Count	2
File Format	PDF
ISBN	1595930590
DOI	10.1145/1167350.1167352
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-03-18
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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