Bioinformatics commercial opportunities

{{#security:edit|Mik Black,Sven}} {{#security:*|Mik Black, Sven}}

• Possiblity of developing a commercial enterprise involving the provision of technical support and training in the setting up of open source project/content management systems.
  • Possible clients:
    • Businesses (e.g., companies trading in something tangible).
    • Research-based institutes (e.g., CRIs, universities).

- internal wiki, internal web portal (e.g., plone, mambo, monotone, joomla, R etc). Open source operating system, Ubuntu. Remote technical support using open source VNC, and Skype.

Selling feature : Make use of tried and tested open source software already out there to minimize software licensing costs. All content is managed in an open source document management framework, including semi-automated scripts allowing reinstallation of software with comprehensive documentation (using ActivePerl).

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Microarray bioinformatics expertise

Overview

Collectively we have over ten years experience in spotted and Affymetrix microarray design and analysis. We are all trained statisticians with a broad range of classical statistical and bioinformatics skills. This expertise includes skills using the R/Bioconductor framework for data organization, exploration, normalization, and analysis using cutting edge algorithm methods.

We are able to offer:

• Good understanding of the underlying science behind microarray technology.
• Development of new methodology for the analysis of microarray data in Bioconductor.
• Experience with different data visualization quality control and exploration methods for summarizing experimental information.
• Use of robust analysis methods which have higher statistical power by incorporating between gene information.
• Conceptual organization of phenotype and genotype information from a statistical design perspective.
• Experience with data and algorithm memory limitations in the R programming environment depending on computing architecture used.
• Ability to provide functional analysis using putative pathway information.
• Experience with QTL mapping analysis.
• Use a collaborative framework which allows fast prototyping of microarray information for future database incorporation.
• Can provide output tailored to the needs of the client.