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Tag Archives: PubMed

Database query and ranked results

The Autophagy network extracted from the recen...
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Already some time ago I’ve  read a piece by Marcelo Calbucci: Is it a database or a search engine?. While it deals with search information within a real estate database, I think his comments are applicable in the many areas of life sciences.

In short, Marcelo points out that people miss a lot of interesting entries while looking for a house, because of inflexibility of the query; number of bedrooms, price, distance from some point – these are all set. However, users are flexible and in such case need rather a search engine that gives them close enough answer or allows to specify weight to each filter.

In life sciences we do search for similarities and analogies all the time. Sometimes it’s direct comparison of sequences, on other occasion is high-level meta-comparison between two systems. And while we have various (statistical) metrics of similarities and they sometimes become a part of a database designs, interfaces of biological databases don’t allow to rank query results according to these metrics. For example I can easily find all human proteins related to disease X or disease Y or disease Z, although I cannot specify that I want proteins related to Z AND Y first on the list. Other example would be searching PubMed – I can look for articles related to “synthetic biology”, but I have no way to specify, that I want papers by James Collins from HHMI AND articles related to these papers to be first on the list. I guess it is possible to obtain such results without going through the whole list, but I doubt the method will be very simple. Filtering still seems to be neglected aspect of database design in life sciences.

My dream biological search engine would have a series of sliders (or ideally, I would like to have a device with series of mechanical knobs attached to the computer) and would allow me to dynamically change weights of various aspects of the query and see immediately how it affects the results. It would be something resembling interactivity of Gapminder World, but on dynamically generated data. Technology and proof of concept seems to be there, but I guess we need to wait quite a few years before this approach will be adopted within life sciences.

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Posted by on January 22, 2009 in bioinformatics, Data mining, Software

 

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Many Eyes and literature summary

I’m not the first one to come up with this idea – Ntino posted about it before. However, I didn’t really understand before how powerful it could be. Using Many Eyes visualization capabilities I’ve created a quick browsable summary of abstracts related to a particular protein. I took all abstracts PubMed returned for a particular query (in this case it was “YadA Yersinia”; YadA is a prominent adhesin and important pathogenicity factor in Yersiniae) and uploaded them as text into Many Eyes. I chose “Word Tree” representation and searched for “yada”, which gave a nice graph of the most prominent phases related to this protein/gene name. Maybe it’s not a breakthrough, but compared to the classification/semantification provided by GoPubMed, such approach works much better for entities that aren’t well described in biological ontologies.

Given that the whole concept is pretty straightforward, it would be nice if one of alternative PubMed search engines provided a similar method of summarizing user’s query, don’t you think?

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Posted by on October 4, 2008 in Papers, Research, Visualization

 

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Mining PubMed – another tools available

There are two new tools available that mine semantically PubMed abstracts, e-LiSe and Anne O’Tate. First one was made by my colleagues from Institute of Biochemistry and Biophysics in Warsaw, while the second is from University of Illinois, Chicago. Female-sounding names is not the only thing that makes them look similar, they both provide analogous functionality, like keywords or author names associated with user query.

There’s quite a lot of third party interfaces to PubMed (see David Rothman’s excellent list), so I couldn’t resist to run few queries on both servers and compare them to GoPubmed, which currently wins hands down in terms of features and interface. I wasn’t surprised to see that results overlap significantly, although not completely. Each of servers found valuable keywords other two did not have – that’s understandable, they use different algorithms. I wonder if we will see a meta-server of PubMed data-miners, like there are for protein structure prediction (for example meta.bioinfo.pl). In theory, exhaustive search for meaningful keywords by different methods and then their classification and analysis should work better than any single method, but this is just a guess.

 
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Posted by on March 5, 2008 in bioinformatics, Data mining, PubMed

 

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Publishers, please provide images in the journal’s feed

Currently almost all scientific journals provide a RSS feed of their content. I am very grateful for that, as many other scientists. However, I see a large disproportion between what I would like to scan through and what I’m actually able to. Abstracts, which are usually provided in these feeds, look almost exactly the same, and after thirty or fifty I’m not really sure if I understand what I read (most likely even Robert Scoble would have the same problem, although at a different level). Biochemistry journal found a solution (see below) – providing images instead of abstracts in the feed (in fact, they used this approach on their homepage long before RSS feeds became a standard). It’s simple, very effective and I have no idea at all why it’s not more popular. So here I’m asking – publishers of scientific journals: please give me images in the journal’s feed. I don’t mind having also the abstracts, but visual summary would be much more useful. In return I promise read these feeds instead of relying on Pubmed searches or my colleagues recommendations and GR shared items.

Feed of Biochemistry journal

 
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Posted by on October 23, 2007 in Papers, PubMed, Research skills

 

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