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Munich Information Center for Protein Sequences
About: Munich Information Center for Protein Sequences is a research topic. Over the lifetime, 79 publications have been published within this topic receiving 6967 citations.
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01 Jan 2001
TL;DR: This chapter gives an overview of available resources on rice bioinformatics and their role in elucidating and propagating biological and genomic information on rice as well as proposed logistics for interlinking these resources.
Abstract: As rice genomics data continue to accumulate at a rapid rate, databases are becoming more valuable for storing and providing access to large and rigorous data sets. This chapter gives an overview of available resources on rice bioinformatics and their role in elucidating and propagating biological and genomic information on rice. Of particular focus here is the informatics infrastructure developed at the Rice Genome Research Program (RGP) following an extensive rice genome analysis. The database named INE (INtegrated Rice Genome Explorer) integrates genetic and physical mapping information with the genome sequence being generated in collaboration with the International Rice Genome Sequencing Project (IRGSP). Database links are initially evaluated using a query tool to explore and compare data across the rice and maize genome databases and for potential application to multiple-crop database querying. A proposed logistics for interlinking these resources is presented to integrate, manipulate, and analyze information on the rice ge-nome. One of the biggest challenges of rice bioinformatics lies in the emerging role of rice as a model system among grass crop species. In view of the importance of comparative genomics in the formulation of new knowledge on plant genome structure and function, bioinformatics remains an essential strategy for gaining new insights into the needs and expectations of rice genomics. Bioinformatics is a new field that emerged in parallel with the advances achieved in genomic analysis. Improved techniques in molecular biology played a key role in catalyzing large-scale sequencing of expressed sequence tags (ESTs), construction of whole genetic maps with specified markers, physical mapping with large insert-size libraries, whole genome sequencing, and transcriptional profiling (Benton 1996). This scenario of rapid technology development combined with mass production of ge-nomic data led to a vital need to transform massive information into more manageable forms by way of bioinformatics. Advances in computer technology including the emergence of the World Wide Web and the Internet, now dominating every aspect of
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