Category Archives: Science

Freerisk – An open platform for risk modeling

By Deepak Singh | Published: June 18, 2009
Image by ynse via Flickr I’ve been meaning to write about Freerisk.org for a while now, but only got reminded yesterday as I read the Wired article about Toby Segaran’s (and Jesper Anderson’s) new project. Freerisk.org sucks in financial data from the SEC using the XBRL format, allows the community to add additional annotations, and then makes [...]
Also posted in Big Data, Computing, Software & Internet | Leave a comment

Hundred nanoseconds a day

By Deepak Singh | Published: June 14, 2009
Image by vitroids via Flickr 100 nanoseconds a day. 100 nanoseconds a day. 100 nanoseconds a day That is amazing. I used to get supercomputing time to do 100 ns simulations during my PhD and those used to last days, but that’s exactly what NAMD has achieved recently. A recent review article by [...]
Also posted in Computing, Life Science, Modeling & Simulation | Tagged , , | 2 Comments

Supercomputing Masterclass – A request for information

By Deepak Singh | Published: June 13, 2009
I have been invited to give a Masterworks talk on Data Challenges in Genomics for Supercomputing 09. I would like to dive into the details about the technical and scientific challenges of high throughput genomics, from microarrays to next gen sequencing and beyond and how we need to be manage these data more efficiently. [...]
Also posted in BioIT, Computing, Event, Informatics, Omics | Leave a comment

TrendingTopics.org: A reference site for data analytics in Hadoop and Hive

By Deepak Singh | Published: June 10, 2009
In episode 21 of Coast to Coast Bio (not yet released) I talk about Hive. For those who may not know, Hive is a data warehouse infrastructure built on top of Hadoop. One of the most recent Amazon Public Data Sets is a sample of Wikipedia page stat statistics by Peter Skomoroch. The full data [...]
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High scale design patterns (missing) in the life sciences

By Deepak Singh | Published: June 10, 2009
I’ve written about software failures in the past. As I get a better understanding of scale and architectures and talk to others about some of the core design principles of systems at scale, e.g. Recover Oriented Computing (also see this talk by James Hamilton), I realize how little most of us in the life science [...]
Also posted in BioIT, Computing, Life Science | Leave a comment

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