Mention kbase. Want to make sequence easy again . Develop in close contact with specific biology projects.
Want to be able to do this without talking to anyone!!
I do not buy into the idea that we can project data analysis and software needs very far into the future.
We are also attacking many other things, including education and training, reproducibility, etc. Also, please stop “developing software for researchers”. We need a more bottom up approach. Maybe mention CaBIG.
An open platform approach to cyberinfrastructure C. Titus Brown firstname.lastname@example.org Asst Professor, Michigan State University (Microbiology, Computer Science, and BEACON)
khmer softwareAn efficient, sensitive, and specific pipeline component for extremely scalable shotgun sequencing analysis github.com/ged-lab/khmer
Academic software development is really, really hard!Considerations of “remixing” are in addition to:• Interesting science• Sufficient compute• User interface• Liability and other legal issues• Integration
Towards an “ecology” of components• We don’t need “one true pipeline.”• We need flexible, reusable, and competing pipeline components.• This is not a concern:• It’s how science works! http://xkcd.com/927/
• Want flexible, sustainable CI? Build open platforms, openly, with open source approaches. – The OSS community has lots of experience in doing this, & working within incentive structures. – Note, traditional academic incentives don’t align well.• Agile methodologies (iterative, use-case driven, organic) ensure that software doesn’t go too far astray; must directly involve (& be driven by) domain research groups.• Too much of software that is produced is not even reusable in theory, much less in practice. This needs to change!!! Blog post will be at: http://ivory.idyll.org/blog/2013-gbmf-mmi.html
Other things I’m doing• Scalable/sensitive/specific algorithms for shotgunomics.• Benchmarking shotgun metagenome assembly.• CI education (NIH/ngs; NSF/data + compute; Sloan/Software Carpentry; BEACON/intro computing for grad)• Hobbies/windmills: – Open science and open data. – Replication and reproducible research. – Changing publication and peer review culture in biology.
Exploratory interfaces for data & executable notebooks