Practical High Throughput Computing for Bioinformatics

14th - 18th April 2008

This course is now closed.

Practical High Throughput Computing for Bioinformatics is a 5-day course covering the use of grid technologies and distributed systems in protein bioinformatics analysis. The course is based at Imperial College London, where it is being jointly run by the Imperial College Bioinformatics Support Service and the London E-Science Centre. This course has been developed thanks to funding from the BBSRC

The course will cover the use of different GRID and collaboration technologies including Sun Grid Engine, Condor and web services for bioinformatics and proteomic tasks. It will consist of a combination of lectures and 'hands-on' practical sessions, along with guest speakers providing case studies of how such technologies are being used in bioinformatics projects. The lectures and practicals making up the course are summarised below:

Lectures

  • Introdution to High Throughput Computing
  • Job Scheduling with Sun Grid Engine
  • Job Scheduling with Condor
  • Globus
  • XML for bioinformatics
  • Distributed Annotation System
  • Introduction to Web Services
  • Future Interfaces
  • Bioinformatics Web Services
  • Guest Lecture: National Grid Service
  • Cluster Design
  • Guest Lecture: EnsEMBL

Practicals

  • Using Sun Grid Engine
  • Using Condor
  • Distributed Annotation System
  • Web Services

The course will run from 14th - 18th April 2008.

The Registration deadline is 7th April for BBSRC funded attendees and 31st March for non-BBSRC funded attendees.

Thanks to funding from the BBSRC, this course is available free of charge (including accomodation) to BBSRC funded post-docs, students and technicians. An administration fee will be charged for non-BBSRC funded participants, which will include refreshments but not accomodation. This fee is £220 for academic attendees, £500 for commercial.

This course is now closed. Please address any queries regarding ongoing BSS courses to bss_help@imperial.ac.uk

 
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