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Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Changing from computing grid to knowledge grid in life-science grid.

Veera Talukdar1, Amit Konar, Ayan Datta

  • 1Department of NCMT, NSHM-Knowledge Campus, Kolkata, India. bhaskarveera95@gmail.com

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|July 7, 2009
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Summary
This summary is machine-generated.

Grid computing offers powerful solutions for life sciences, enabling high-performance computing and large-scale data analysis. This technology integrates distributed resources for complex biological research and knowledge sharing.

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Area of Science:

  • Life Sciences
  • Bioinformatics
  • Computational Biology

Background:

  • Life sciences generate vast amounts of data (e.g., millions of genes) requiring high-performance computing beyond single institutions.
  • Grid computing leverages networked resources for complex problems needing significant processing power or data access.

Purpose of the Study:

  • To review the latest grid technologies for life sciences.
  • To explore computing, data, and knowledge grids.
  • To assess grid computing's potential as a cyber infrastructure for biological research.

Main Methods:

  • Survey of current grid technologies.
  • Analysis of computing grid, data grid, and knowledge grid applications.
  • Conceptual extension from computing to knowledge grids.

Main Results:

  • Computing grid technologies are mature for high-throughput life science problems.
  • Data grid technologies are suitable for creating bioinformatics resourceomes.
  • Knowledge grids facilitate sharing of explicit and tacit knowledge within research communities.

Conclusions:

  • Grid computing is a viable cyber infrastructure for life sciences.
  • Extending grid concepts to knowledge grids enables collaborative knowledge creation and sharing.
  • Grid technologies support both computational and collaborative aspects of modern biological research.