eric.jain.name 

The Google Gadgets API can be used to create small applications that people can add to their personalized Google home page. Here is a simple “gadget” for blasting protein sequences.

Google now allows you to create custom search engines. I used this to set up a search engine that searches in well know life sciences sites.

Got back this week from Brazil where I had spent all of August. Here are some pictures and notes from the trip.

How do you concatenate two huge XML files efficiently without writing any code?

Google Subscribed Links provide a mechanism for adding information at the top of a Google search results page. I set up an example that can be used to see information from the Enzyme Nomenclature Database when searching for something like EC 1.2.3.4.

Just discovered AutoStitch. AutoStitch is an amazing piece of software that assembles a set of images into a single panorama image. This is of course not the first software of this kind. But AutoStitch may be the first that just works (no manual editing of the image overlaps is required) and produces good output even if the source images weren’t shot very carefully and differ in brightness and coloring. Perfect for lazy people like me who use a point-and-shoot camera and couldn’t be bothered to spend a lot of time patching up images.

We’ve been looking for a decent ontology editor for a while now. The problem is that most editors are either to technical or too cumbersome to use for entering a lot of data. But it looks like we have finally found something suitable!

According to this paper the most influential criteria engineers and scientists use for selecting information resources are not quality or even familiarity but 1. the time it takes to track down information and 2. the authoritativeness of the resource. Perhaps this explains why researchers are increasingly using Google Scholar rather than PubMed (PubMed is more authoritative, but Google’s ranked results allow you to find publications faster) and why the NCBI still receives more requests for protein-related data than we do (both sites are equally bad at searching, but NCBI may be seen as more authoritative).

Much has been said about (and blamed upon) communication problems between biologists and computer scientists. But after attending a meeting with biologists and computer scientists this week, I am starting to suspect that the problem isn’t just communication.

We are currently exploring various strategies to encourage people to let us know when they find errors or omissions in UniProt, or even to contribute data as they publish their research, rather than waiting for a curator to pick up their results from a publication.