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Trends in life science grid: from computing grid to knowledge grid.

Akihiko Konagaya¹

¹Genomic Sciences Center, RIKEN, Yokohama, Japan. konagaya@gsc.riken.jp

BMC Bioinformatics

|January 27, 2007

Summary

Grid computing offers powerful cyberinfrastructure for life sciences, advancing high-throughput computing and data handling. Extending to knowledge grids enables collaborative knowledge creation and sharing within scientific communities.

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Area of Science:

Life Sciences
Bioinformatics
Cyberinfrastructure

Background:

Life sciences increasingly require high-performance computing and large data handling capabilities.
Single institutions often lack the necessary computational resources.
Grid computing presents a scalable solution for these demands.

Purpose of the Study:

To review the latest advancements in grid technologies.
To explore the potential of computing, data, and knowledge grids in life sciences.
To discuss the evolution of grid concepts towards collaborative knowledge sharing.

Main Methods:

Survey of current grid technologies.
Analysis of computing grid maturity for life science problems.
Evaluation of data grid applications in bioinformatics.
Conceptualization of knowledge grids for community collaboration.

Main Results:

Computing grid technologies are sufficiently mature for high-throughput life science applications.
Data grids show strong potential for creating comprehensive bioinformatics resourceome.
Knowledge grids require community involvement for sharing both explicit and tacit knowledge.

Conclusions:

Grid computing extends beyond resource sharing to facilitate collaborative knowledge creation and experience exchange.
The concept of grid can evolve into a shared space for scientific communities to work and learn together.
Integrating knowledge grids enhances the utility of grid infrastructure for scientific advancement.