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Recently I wrote about PubReMiner, an online application designed to help you search PubMed. Now I present a similar and even more powerful application named GoPubMed.


When you search PubMed the conventional way, via the Entrez system, two things happen. First your query is translated with identification of Medical Subject Headings (MeSH) terms and secondly this translated query is matched with words from all the abstracts. The second part is performed by term matching, which ultimately means that keyword synonyms are not used in the search. This way you can lose a lot of important articles. Finally, found abstracts are listed in the reverse chronological order. In most of the cases this is not what you want, and you are forced to manually go through all the abstracts to find those relevant to you.  

GopubmedGoPubMed can help you with the mentioned problems. When you submit the query, it retrieves the abstracts from PubMed but then does something extra. It categorizes them based on the relevance provided by the ontology terms used in MeSH and Gene Ontology (GO). Results are sorted in 4 categories: what, who, where and when. The what category is where abstracts are sorted according to the concept hierarchies of GO and MeSH enabling the combined search in molecular biology and medicine. This helps to systematically explore the results. The who category helps you identify leading scientists and centers in specific biomedical areas. The where category provides information about geographic localization of persons, centres, universities, together with journals in which found papers were published. Finally, the when category is all about distribution of publications through time.

To use GoPubMed simply enter the search query like you were using Entrez. After completing the search GoPubMed will inform you of the total number of articles found, and by default analyze the latest 1 000 abstracts. You can then go through these abstracts, choose to show statistics for these results or refine your search using the 4 categories (what, who, where and when). Choosing to show statistics will analyze results according to the 4 categories and present them in a clear manner. Especially interesting are graphs, depicting publications over time, and maps, indicating localizations of authors.  World map

I like the design of the application, it feels very web 2.0. It takes some time to get used to it, but after a short learning period you start to enjoy it. This feeling is even more reinforced when you get good search results and ideas how to use it creatively start popping to your mind. 

Here are some examples of the ways you can use GoPubMed, as proposed by the authors. I am sure you can come up with others to really boost your PubMed search. 

Which diseases are associated with HIV?

Type “HIV”. Go to “What” and click on “more of Diseases”. Among others hepatitis and tuberculosis are mentioned. Clicking on tuberculosis retrieves the relevant articles including statements such as “Despite the synergy between the human immunodeficiency virus (HIV) and tuberculosis (TB) epidemics, the public health responses have largely been separate”.

Where are leading centers and who are scientists for liver transplantation in Germany?

Type “liver transplantation Germany[AD]”. At the top of the “Who” category the result shows the top author “Neuhaus P” and the city is “Berlin”. Prof. Peter Neuhaus works at the Charite Hospital in Berlin, Germany, is a leading specialist in the field.

Do you know in which topics Craig C. Mello and Andrew Z. Fire are working on?

Search for “Mello C[au] Fire A[au]”. Now inspect What, Where, Who and When categories!
Following the top categories the answer is automatically extracted:
Caenorhabditis elegans
RNA, Double-Stranded
RNA interference

Which disease is rhodopsin involved in?

Search for “rhodopsin ” and in just one mouse click on “Diseases ” your question is quickly found.
The group of more important diseases related to rhodopsin are shown under this ontological category.
Retinal Degeneration
Retinitis Pigmentosa

Which biological processes are inhibited by aspirin?

Search for “aspirin inhibits ”.
By inspecting the most frequent term “biological processes ” you can very quickly understand that “cyclooxygenase pathway ” is the pathway related to this biological process. GoPubmed found more than 30% papers verifying that “cyclooxygenase pathway ” is inhibited by aspirin.

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PubMed provides access to Medline, a premier bibliographic database that contains references to journal articles in the life sciences with a concentration on biomedicine. It is available via the NCBI Entrez retrieval system, which was developed by the National Center for Biotechnology Information (NCBI) at the National Library of Medicine (NLM), located at the U.S. National Institutes of Health (NIH). 

PubMed is extremely popular among biomedical researchers, in part because it offers free access, contrary to other such search engines like Scopus and Web of Science. However, during the years I heard a lot of people complaining about PubMed. They do not like its interface and are not satisfied with search results it provides. A lot of these people never gave any thought about PubMed, nor did they try to learn how to use it properly. They just punch in queries like they do on Google. I believe that a lot can be improved by understanding of Medline and especially of the MeSH (Medical Subject Headings) controlled vocabulary used to index all Medline articles. Users should also use tags, booleans operators and limitations, which can make the whole search process more pleasant and satisfactory. I highly recommend going through the PubMed online training, which also offers easy to follow animated tutorials with sound.

However, I would like to present a different approach to searching PubMed, an online application named PubReMiner. I had an opportunity to see a presentation of PubReMiner during my stay at the Academic Medical Center (AMC) in Amsterdam last summer, and was immediately delighted by it. Instantaneously I realized how beneficial it could be during my future search for literature. 

PubReMiner was created by Jan Koster, a member of Bio-informatics team of the Department of Human Genetics at the AMC, with a purpose to help people find biomedical literature on a certain subject indexed by the PubMed database. PubMed is growing larger everyday and when you enter a search term on any subject, it is highly likely that you will end up with a huge number of references and a headache. To get something useful to work with you need to combine different keywords, but usually you do not know which ones. Here is were PubReMiner steps in. It allows you to initiate a broad query (which is currently restricted to 7.500 abstracts), after which you can add or exclude words, authors, and journals to guide your search. These are all displayed in descending order, allowing you to immediately see which words, authors, and journals are used the most in combination with your query, so you can use them in your search. Apart for allowing the construction of efficient queries, PubReMiner can be useful in other areas, and this is actually how I use it the most. These are:

  • Selection of a journal for your current work (by scanning the most often used journals of similar research)
  • Finding experts in a research area (by viewing the authors associated with your query)
  • Determination of the research interest of an author (by viewing the keywords associated with an author) 

The best way to get the idea about PubReMiner is, of course, to try it yourself. Nevertheless, I will post a simple demonstration enriched by screen shots to get you started. 

Let’s say for example that you were reading the new issue of Nature and read the article entitled “Proteasome subunit Rpn13 is a novel ubiquitin receptor” by Koraljka Husnjak, Suzanne Elsasser, Naixia Zhang, Xiang Chen, Leah Randles, Yuan Shi, Kay Hofmann, Kylie J. Walters, Daniel Finley & Ivan Dikic. You were very intrigued by the research, so you decided to learn more about this research group and their work. You start you investigation with the last author, knowing that he might be the leader of the group. 

Go to PubReMiner and enter “dikic i” into the search box.


Your query results in 99 references. 
PubReMinerThis is way too much for you to start reading it all, but you can already learn a lot about the author. You can see for example the number of publications he has published per year, in which journals and who were his most frequent coauthors. Also, you can see which words, Mesh terms and substances are used in combination with this author, and this can help you identify his research interests. In just a matter of seconds you came to know that this author is, among others, interested in phosphorylation, signal transduction and ubiquitin/metabolism. 

The article you read was about ubiquitin, and this is the subject you are most interested in, so you select Ubiquitin/metabolism Mesh term and search again. 


Again, you get a lot of information in a structured table about Ivan Dikic’s work on ubiquitin. This is still too much for you to read, so you select only his most recent work, the last two years (2007 & 2008).


 This query gives you 5 references, which you feel is just the perfect number for you to start learning more, so you click on theGoTo PubMed with query button. 


The button does what it promises to do, which is opening PubMed in new window with your search query and 5 references.


This is just a small part of what PubReMiner has to offer, but I hope I managed to at least show you some basic and encourage you to try it.  

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