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Archive for 3rd Party PubMed/MEDLINE Tools

PubMed Faceoff

PostGenomic’s PubMed Faceoff is the first 3rd Party PubMed/MEDLINE Tool I’ve looked at that really made me chuckle.

This site applies a simple, photorealistic variant of the Chernoff Faces visualization technique to impact factor data for papers in the PubMed database of biomedical literature.

Basically it allows you to search PubMed and have the results represented as a set of human faces.

Each paper is represented as a face. The ethnicity and gender of the face is selected at random for visual interest – you can turn this feature off if you so choose.

The age of a face correlates with the publication date of the paper. Younger faces are more recent papers.

A smile means that the paper has been cited more times than expected (based on its age). Larger smiles mean more citations.

A frown means that the paper has been cited far less than you might expect.

The raised eyebrows correlate with the impact factor (sort of – actually the Eigenfactor) of the journal in which the paper was published.

Some example search results:

I absolutely appreciate the concept (potentially being able to estimate several properties of an article at a glance)- it’s just that some of the facial expressions crack me up.

CoPub

http://services.nbic.nl/cgi-bin/copub/CoPub.pl

CoPub is a text mining tool that detects co-occuring biomedical concepts in abstracts from the Medline literature database. The biomedical concepts included in CoPub are all human, mouse and rat genes, furthermore biological processes, molecular functions and cellular components from Gene Ontology, and also liver pathologies, diseases, drugs and pathways. Altogether more than 250,000 search strings are linked with CoPub.

Special attention was given to genes and proteins. For all human, mouse and rat genes not only long forms of names were used, but also their symbols and aliases, which increases recall. Symbols not referring to genes or proteins are a well known problem, but sophisticated scripts detect these homonyms and neglect the abstracts in which they occur thereby increasing precision.

Features include:

* Fast and easy access to relevant abstracts
* Single gene search in all categories
* Multiple gene search in all categories
* Single keyword search in gene category
* Categories of biomedical concepts: genes (human, mouse, rat), liver pathologies, biological processes, molecular functions, cellular components, diseases, drugs, pathways
* Use of long forms, symbols and aliases of genes
* Homonym detection
* Statistical filter to display only significant biomedical concepts
* Based on Medline abstracts till February 2008

MiSearch: Adaptive PubMed Search Tool

http://misearch.ncibi.org/

From MiSearch Help:

“MiSearch works with NCBI Entrez and your history of browsing to build a profile of your areas of interest, and uses this information to rank citations likely to be of most most information to you at the top of the list.”

“MiSearch uses a classification algorithm based on MeSH term, substance names and author names associated with citations. Two sets are defined. One is the set of articles you have previously clicked on to view. The other is all of PubMed. For each citation in the retrieval set, the algorithm calculates the likelihood that the citation is a member of these two sets. Article having the highest likelihood of belonging to the set of articles you have viewed are ranked at the top of the list.

The “User” field is used as an identifier to track usage. If you do not provide a name, the IP address of your request will be used as a default. If you know you will be doing searches for different tasks with different subject areas, feel free to define a “User” for each task.”

Slides from an MLA 2008 presentation by NLM Associate Fellow Marisa Conte

MLA 2008: Plenary Session IV Slides

David Rothman

Amanda Etches-Johnson

Melissa Rethlefsen

Bart Ragon

PubGet (3rd Party PubMed/MEDLINE Tool)

The idea behind Pubget is that it speeds up the process of grabbing the full-text PDFs from PubMed search results. The videos below illustrate the idea:


Above: Embedded video. If you are reading this in an aggregator, you may need to visit the site to view the video.

If you’re at one of the following institutions, you can try a full-featured Pubget that links to full-text PDFs available to these institutions:

From Pubget’s public site, you can get a feel for how it works, but it’ll only pull up open access PDFs.

To keep up on new developments, you can subscribe to the feed of the Pubget blog.

Interested in getting this service for your library’s users? Get in touch and let them know you’re interested.

JANE, eTBLAST, and Whatizit

When I posted in February about JANE, I should also have mentioned eTBLAST(previously mentioned here):

Our service is very different from PubMed. While PubMed searches for “keywords”, our search engine lets you input an entire paragraph and returns MEDLINE abstracts that are similar to it. This is something like PubMed’s “Related Articles” feature, only better because it runs on your unique set of interests. For example, input the abstract of an unpublished paper or a grant proposal into our engine, and with the touch of a button you’ll be able to find every abstract in MEDLINE dealing with your topic. No more guessing whether your set of keywords has found all the right papers. No more sorting through hundreds of papers you don’t care about to find the handful you were looking for–our search engine does it for you.

I also recently stumbled across Whatizit:

Whatizit is a text processing system that allows you to do textmining tasks on text. The tasks come defined by the pipelines in the drop down list of the above window and the text can be pasted in the text area. The description of each individual task/pipeline can be found following the link next to the submit button. Whatizit is also a Medline abstracts retrieval/search engine. Instead of providing the text by Copy&Paste, you can launch a Medline search. The abstracts that match your search critetia are retrieved and processed by a pipeline of your choice.

When the user actually *is* broken (Anna Kushnir and PubMed)

I have distinct childhood memories of asking my mother what one word or another meant. She would point out that there was a dictionary close at hand designed exactly for that purpose and invite me to make use of it.

I remember asking my father to teach me to program in BASIC. He cheerfully agreed and handed me the big brown manual.

So maybe I’m weird and so are my folks, but these memories inform my take on the chatter in the blogosphere and on MEDLIB-L about this post by Harvard PhD student Anna Kushnir in which she expresses her frustration with PubMed. Kushnir writes (in part):

“I hate PubMed. I hate it with a burning passion. For a site that is as vital to scientific progress as PubMed is, their search engine is shamefully bad. It’s embarrassingly, frustratingly, painfully bad.”

[...]

“Why is PubMed so behind the times? Why? How does it even work? Does it search only the abstract? Does it also search the body of the papers that are available online? Why does it get so massively confused by an author’s initials and last name together, in one search? Why can’t it alert me when papers relevant to my work are published?”

I’m the first to admit that PubMed has problems and much room for enhancement, but if Kushnir had bothered to look at PubMed’s help manual or try some of its excellent tutorials she’d have learned exactly how it works, what PubMed indexes, how she can search by author, and that it can alert the user when papers relevant to her work are published via email or RSS.

So while PubMed has real, legitimate problems, Kushnir’s complaints don’t really touch on any of them. She could’ve resolved the problems she notes by flipping through the well-written, clearly laid-out, easy-to-navigate manual.

A number of helpful people who are much nicer than I am left useful comments for Kushnir.

Medical librarian Kathleen Crea offered a clear explanation of how articles are indexed and what MeSH is.

Medical librarian Rachel Walden even offered to help remotely with specific searches if Kushnir didn’t have a Harvard medical librarian handy.

But Kushnir decided that none of this really helped and later commented:

I don’t think I should have to be, or enlist the services of, a medical librarian in order to do a simple search on a literature search engine. PubMed should be an intuitive search engine such as Google, or others. I don’t know of many researchers, either MDs or PhDs, who have had extensive training in computer science or search algorithms. I am going to go out on a limb and say that I am representative of many other biomedical researchers in my struggles with PubMed. I am trained in Cell Biology and Virology. PubMed should be tuned to my needs and my skill set. I should not have to tune to it. Harsh as it may sound, PubMed is most useful for biomedical professionals, not for medical librarians or for computer scientists. Yes, if I devoted an afternoon or more to learning the system I dare say I would become a proficient, but my question stands – why should I have to?

Huh.

The index of biomedical literature searched from PubMed is a vast and complex set of data. Any tool that will search it effectively for very specific needs will necessarily be complex. If Ms. Kushnir doubts this, perhaps she should perhaps try any other interface for the same data. Some other interfaces work better for some purposes and some users, but all are complex.

Using PubMed does not require “extensive training in computer science or search algorithms,” it requires reading the manual. Kushnir actually admits that if she “devoted an afternoon or more to learning the system” she would “become a proficient,” and yet she fails to recognize her complaints as the whining they are.

Kushnir writes at JOVE:

My rant somehow wound up on a medical librarian listserv and they came out in force defending NCBI and PubMed, listing pages and pages of helpful and warm instructions and hints on how to make it do what I need it to do, pages of suggestions, with offers of hands-on assistance and training, which have all been wonderful. Occasionally though, they were biting and harsh, saying that if I only knew what I was doing (and only if I weren’t so ignorant… yup, ignorant), PubMed would seem to me the greatest thing ever.

I’m not criticizing Kushnir’s ignorance and would take issue with those who did. Ignorance, once identified, should alert the librarian to a teaching opportunity- not an occasion for shaming. Criticizing the extraordinary laziness in her refusal to receive help from a librarian or to take a quick look at the manual, though? That’s fair game.

Kushnir continues:

I am a research scientist by long, hard training. I am a fairly web-savvy research scientist, and still, I have trouble with PubMed.

As a medical librarian friend recently pointed out to me, it requires instruction to learn to drive a car. Kushnir is unwilling to read the manual and wants to blame PubMed/NLM for her difficulties. Kushnir talks about having spent hours trying to get PubMed to do what she wants, but declines help from multiple medical librarians who’re happy to teach her and can’t be bothered to invest 30 minutes in reading from the manual because it should, in her thinking, be possible to do without any effort on her part.

Kushnir continues:

The search engine is not made for medical librarians. It’s not made for computer programmers. It’s made for scientists, to be used by scientists, needed most by scientists.

Actually, Medline’s history is that it was made primarily for medical librarians and secondarily for physicians, but that’s not really important.

It should be easy for scientists, goofy, only moderately-computer literate scientists, to use. It should be intuitive (read: Google), it should not have a ginormous page of inscrutable instructions, it should not require the hour-long training sessions, kindly offered at most medical libraries. It should be plug and chug.

I might just as well argue that the tools of virology research should be intuitive to me. After all, I’m a very computer-literate, Web-savvy biomedical information professional. Why should I need her years of training to understand her work?1

“Inscrutable?”
Kushnir also describes PubMed’s help documentation as “inscrutable.” When I was teaching myself how to use PubMed, I found the documentation clear and helpful, so this surprised me. I decided to run the PubMed Quick Start document through Google Docs’ analysis:

Let’s review these scores:

Flesch Reading Ease: 62.97
(A score from 60-69 is considered “standard”)

Flesch-Kincaid Grade Level: 5.00
(Fifth grade)

Automated Readability Index: 5.00
(Again, fifth grade)

So it would appear that the help documentation is written at a fifth-grade level. I find it hard to believe that a PhD student at Harvard cannot read at a fifth-grade level, so I’m left with the impression that Ms. Kushnir didn’t actually attempt to read any of the documentation before declaring it “inscrutable.”

Suggestions for Ms. Kushnir and other research scientists who don’t like reading the instructions:

So the tool is necessarily complex because the data it searches is complex and the user refuses to read the well-written help documentation or accept help from a friendly librarian (even when multiple librarians are reaching out across thousands of physical miles of distance and the gulf of the patron’s unwillingness to learn).

I can only conclude that sometimes the user *is* broken.2

Thank you to the two medical librarian friends who read the first draft of this post and offered comments.


1 Hint: Because the work is complex and involves a skill set that grows (with effort) over time.

2 See Karen Schneider’s excellent post, “The User is Not Broken”.

More PubMed for Facebook

Gerry McKiernan points out two Facebook applications for searching PubMed, PubFace and PubMed Search.

PubFace Results:

PubMed Search Results:

It’s sort of neat to be able to quickly share a PubMed citation with another Facebook user (see the link in the PubFace results above for “Send to a friend” or PubMed Search’s “Share this” button) and it is handy to be able to add citations to a collection (see PubFace’s “Add to MyLibrary” links or PubMed Search’s “add this to your favorites”)… but I’m having trouble seeing how it is preferable to using PubMed itself and making use of MyNCBI or “Send to email”…or using a powerful bookmarking tool like del.icio.us, Connotea or CiteULike.

I’m only a casual Facebook user, so it is entirely possible I’m missing something. If so, please clue me in? Thanks!

Making PubMed “Easy”?

Jon Brassey writes:

I may have missed something, but none of these alternate interfaces allow easy searching of PubMed. Some are wonders of programming, some allow some very neat tricks but none make searching of PubMed easy.

That’s a fair criticism, I suppose. I think that although PubMed has come a very long way in developing tools that make searching the NLM’s databases easier for medical librarians, clinicians and consumers, it still takes some knowledge and skill to perform a really useful search of the primary literature.

Jon continues:

I suppose my biggest issue with PubMed is that doing a search of statins returns 18,491 results. Unpicking that a bit:

* Most research shows search engine users finish looking after 3 pages of results.
* From our own experience with TRIP we also know that most users only use single search terms (e.g. asthma, hypertension).

So what I’m saying is that statins is a realistic search term and that suggests that 18,431 (18491-60) results are superfluous.

Therefore, the two challenges to me are:

* Return fewer results in the first place
* Allow users to easily qualify their searches.

Let’s bring Jon’s challenges to Healia’s PubMed/MEDLINE Search. It isn’t my favorite, but if Jon uses it to search for statins, he’ll see that, at the time of this writing, only 7,731 results are returned1 and that there are a number of tools for “qualifying” the search right there on the search results page.

You can adjust for date:

You can filter for review articles or for English language articles only:

You can filter by patient demographics:

Healia even recognizes that we’re searching about a class of drugs and gives us tabs so we can filter by Dosage, Usage, or Side Effects:

So let us assume that Jon’s hypothetical user wants to see English-language review articles about the dosage of statins from only the last 5 years. That’s only twelve results. I think this passes Jon’s test.

With that out of the way, I need to add:

Criticizing PubMed for returning too many search results for a query as inadequate as “statins” seems unreasonable to me. A major part of what makes PubMed an amazing tool is its complexity. I believe and hope that new tools will continue to be developed that make the data useful to various kinds of users in various new ways, but I don’t expect that getting exactly what one wants from the primary literature will ever truly be “easy.”


1 I’m guessing that the reason why PubMed returns 18,431 results and Healia’s PubMed/MEDLINE search returns only 7,731 is that Healia’s search is only looking for the string statins.

PubMed, on the other hand, translates statins into “hydroxymethylglutaryl-coa reductase inhibitors”[MeSH Terms] OR “hydroxymethylglutaryl-coa reductase inhibitors”[Pharmacological Action] OR statins[Text Word].

After all, if we search PubMed for “statins” as a string, we get only 7,990 results.

MScanner: a classifier for retrieving Medline citations

MScanner: a classifier for retrieving Medline citations
Graham L Poulter, Daniel L Rubin, Russ B Altman and Cathal Seoighe
BMC Bioinformatics 2008, 9:108doi:10.1186/1471-2105-9-108
Published: 19 February 2008

Free full text: [PDF]

Article is about a third-party PubMed/MEDLINE tool that I have not been able to make work, MScanner.

[Other posts about third-party PubMed/MEDLINE tools]

Article about Anne O’Tate (3rd Party PubMed/MEDLINE Tool)

Free full text article (PDF) from the Journal of Biomedical Discovery and Collaboration on Anne O’Tate.

In this paper, we present Anne O’Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the “most important” words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles.

(Hat tip: ResourceShelf)

You can find other posts about 3rd Party PubMed/MEDLINE tools here.

More details: NLM Browser Toolbar

I posted earlier this month about a browser toolbar built to make use of NLM resources.

At the time I was impressed with Guus van den Brekel for having discovered it. It turns out that I have better reason to be impressed. Guus built it.

I finally got around to trying it…and I like it. I’m not sure that the “Other PubMeds” feature is really worth the real estate it takes up (I’d rather it linked directly to particularly useful 3rd-party PubMed Tools rather than to sites about them), but that’s a fairly minor complaint.

Conduit appears to have a good reputation and I absolutely trust Guus- so I’d say it is worth trying whether or not it has been endorsed by the NLM. If you have suggestions about how it could be improved, please share them with Guus.

JANE (Journal/Author Name Estimator)

Have you recently written a paper, but you’re not sure to which journal you should submit it? Or are you an editor, and do you need to find reviewers for a particular paper? Jane can help!

Just enter the title and/or abstract of the paper in the box, and click on ‘Find journals’ or ‘Find authors’. Jane will then compare your document to millions of documents in Medline to find the best matching journals or authors.

http://biosemantics.org/jane/

More info:
Martijn J. Schuemie and Jan A. Kors, Jane: Suggesting Journals, Finding Experts, Bioinformatics, January 28, 2008.

[via]

Other posts about third-party PubMed/MEDLINE tools

NLM Browser Toolbar

http://nlm.ourtoolbar.com/

This appears to be a Conduit toolbar…but I see no proof that the NLM is actually behind it.

If you install it and use it, leave a comment to let me know what you think of it?

[Via Guus van den Brekel]

My Resource Review of BioWizard (JMLA)

Big day for me. My Electronic Resources Review of BioWizard was published in the JMLA.

BioWizard
David L. Rothman
J Med Libr Assoc. 2008 January; 96(1): 74. doi: 10.3163/1536-5050.96.1.74.
| Full Text | PDF–988K

Of course, I just realized that BioWizard has significantly changed its interface since I wrote the review. Dangit.

BiomedExperts.com, ListServs and The Wrong Orifice

So, from the start I thought BiomedExperts sounded like a pretty neat idea- a social network wherein personal profiles are built with data from PubMed.

From the FAQ:

“Profiles in BioMedExperts (BME) are generated by extracting and assigning the biomedical concepts from an article to the authors and co-authors that are listed with the published article. We have done this on six million scientific publications from over 6,500 journals. BME currently contains profiles of about 1.4 million biomedical experts from more than 150 countries, representing approximately 12 million connections in the pre-established BME network. BME experts can access the system to revise and/or update their personal details, publications and/or preferences”

Huh. Neat. Definitely worth checking out.1

Before I got around to checking it out, though, a discussion blossomed via the Web4Lib listserv. Gerry MckKernan started things out by sharing the known details.

Tom Peters wrote, quite reasonably:

“…Yes, if this proves successful, I think similar things could be created for other disciplines.”

…to which Thomas Krichel replied:

“and another set of nails on the coffins of libraries.”

Whhhaaaaa…? I was baffled- but It seems I wasn’t alone. Jesse Ephraim made me smile with his reply to Thomas Krichel:

“If something like that is a set of nails on the coffins of libraries,then libraries deserve to die out.

We need to quit thinking of these things as challenges to our domain, and start looking at other ways that we can be useful.

Adaptation and change will be the norm from now on.”

I decided upon reading this that I would like to buy Jesse the beverage of his choosing for being so unapologetically correct.

But Thomas Krichel wasn’t done:

“Tell me, if all biomedical scientists were to use biomedexperts, why would the US government still fund PubMed?”

Why WOULDN’T they? BiomedExperts doesn’t compete with PubMed/MEDLINE. Rather, it RELIES on PubMed/MEDLINE. If Mr. Krichel is going to play chicken little, perhaps he could try actually *looking* at the sky before pronouncing it to be in free-fall?

But this was the part that bugged me the most. Jesse Ephraim had said (rightly, I think) that “[a]daptation and change will be the norm from now on.”

Thomas Krichel retorted:

“Go and tell that to the NLM. I am not sure they will obey, but it’s worth a try.”

Again: Whhhaaaaa…? It is far from perfect, but I think PubMed exemplifies pretty well a tool that is constantly adapting, constantly changing. Some days I wish it changed and adapted less. My point: There are privately-funded institutions that innovate a hell of a lot less. Anyone who works in a health sciences library knows how much the NLM has accomplished and continues to accomplish.

I guess I can’t really blame Krichel for not knowing this. A quick look at his C.V. seems to indicate that he doesn’t work with biomedical literature or in a health sciences library- so he can’t be expected to speak knowledgeably about the NLM.

Only on listservs and blogs can you see supposedly educated people speak completely out of the wrong orifice in this manner.

Anyway. As an example, check out T. Scott Plutchak’s profile in BiomedExperts.
t_scottprofilebme.png
(Click on thumbnail for full-size image.)


1 Tangent: A medical librarian friend describes it to me as “really just an advertisement for Collexis” and its “INCREDIBLY expensive” products. I haven’t looked into that…but even if that’s true, it doesn’t mean that BiomedExperts can’t be useful.

Compare-stuff.com/pubmed

I haven’t decided yet if this third party PubMed tool will prove to be of any practical use to me, but I had fun playing with it.

In the screen capture below, you can see where I asked the tool to count up all the records in PubMed containing the string “internet” and compare the counts by year from 1999 through 2006.


Click this image to see the full-size results

_________
Click here for other posts in the ‘Third-Party PubMed/MEDLINE Tools’ category

Poster on Smorgasbord of PubMed Alternate Interfaces

Margaret Henderson left a comment to let me know that she presented a poster at the Mid-Atlantic Chapter, MLA meeting on Alternate PubMed Interfaces.

I’d like to add that “A Smorgasbord of PubMed Interfaces” is as wonderful a title for a poster as I’ve ever heard.

You can download a PDF of the poster here and download some additional details in the the handout (.doc) here. Best of all, there’s a Web page made from the same material here.

_____

Previous posts from davidrothman.net in the Category of 3rd-party PubMed/MEDLINE tools

Poster: PubMed Alternative Interfaces

From the Wiki des Bibliothèques Universitaires de Médecine et Santé Publique – Lausanne, check out this great poster on Alternative interfaces for PubMed searches by Isabelle de Kaenel and Pablo Iriarte.

Thanks for pointing this out, Gaétan!

Other posts about Third-Party PubMed/MEDLINE Tools

(Perhaps it is time I made this a WordPress category…?)

Pubconn (Firefox Plugin for Connotea in PubMed)

If you use Connotea, Pubconn might be a useful tool.

Different scenarios in which Pubconn might prove useful:

- When you are doing a Pubmed search, you are interested to see if other people have bookmarked any of the papers you have in your search results. Currently, you should query Connotea for each and every record returned by Pubmed. Using Pubconn, any of the Pubmed records that have been bookmarked are highlighted within your search results.

- You are doing a search in Pubmed and find an article familiar to you. Have you bookmarked this paper before? Currently, the best way to do this is to have a Connotea page open and search for the Pubmed record in your bookmarks (e.g. using PMID), or press the ‘add to Connotea’ button to see if you have already bookmarked that paper; the latter option is severly limited due to Buggotea . Using Pubconn, your bookmarked records in Pubmed are highlighted and the tags and descriptions you have provided for the bookmarked are displayed next to the Pubmed record.

- You are doing a literature review in a collaborative project with several other people, you have created a user group in Connotea and are bookmarking relevant papers in that group. When you start searching, you are interested in knowing whether a particular paper has already been reviewed by one of your teammates. Using Pubconn, all the bookmarks highlighted by your colleagues are highlighted.

Screen captures:


Unfortunately, the Google, Google Scholar and Clipboard buttons don’t work for me.

See Also: PubMed2Connotea

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