The problem with posters at academic conferences

I recently attended the Genome Science: Biology, Technology, and Bioinformatics meeting in the UK, where I presented a poster. As I was walking around, looking at other people's posters, I was reminded of the common problem that occurs with many academic posters. Here are some pseudo-anonomous examples to show what I mean (click images to enlarge):

The problem here is not with the total amount of text — though that can sometimes be an issue — but with the width of the text. These posters are 84 cm (33 inches) wide, and it is not ideal to create text blocks that span the entire width of the poster. The reasons behind this are the same reasons why you never see newspapers display text like this…we are not very good at reading information in this manner.

To quote from Lynch & Horton's Web Style Guide; specifically the section on Page Width and Line Length:

The ideal line length for text layout is based on the physiology of the human eye. The area of the retina used for tasks requiring high visual acuity is called the macula. The macula is small, typically less than 15 percent of the area of the retina. At normal reading distances the arc of the visual field covered by the macula is only a few inches wide—about the width of a well-designed column of text, or about twelve words per line. Research shows that reading slows as line lengths begin to exceed the ideal width, because the reader then needs to use the muscles of the eye or neck to track from the end of one line to the beginning of the next line. If the eye must traverse great distances on a page, the reader must hunt for the beginning of the next line.

In contrast to the above examples, there were a couple of posters at the #UKGS2014 meeting that I thought were beautifully displayed. Bright, colorful, clearly laid out, not too much text, and good use of big fonts. Congratulations to Warry Owen et al. and Karim Gharbi et al. for your poster presentation prowess!

When is a citation not a citation?

Today I received a notification from Google Scholar that one of my papers had been cited. I often have a quick look at such papers to see how our work is being referenced. The article in question was from the Proceedings of the 3rd Annual Symposium on Biological Data Visualization: Data Analysis and Redesign Contests:

FixingTIM: interactive exploration of sequence and structural data to identify functional mutations in protein families

The paper describes a tool that helps "identify protein mutations across a family of structural models and to help discover the effect of these mutations on protein function". I was a bit surprised by this because this isn't a topic that I've published on. So I looked to see what paper of mine was being cited and how it was being cited. Here is the relevant sentence from the background section of the paper:

To improve the exploration process, many efforts have been made, from folding the sequences through classification [1,2], to tools for 3D view exploration [3] and to web-based applications which present large amounts of information to the users [4].

Citation number 2 is the paper on which I am a co-author:

  • Chen N, Harris TW, Antoshechkin I, Bastiani C, Bieri T, Blasiar D, Bradnam K, Canaran P, Chan J, Chen C, Chen WJ, Cunningham F, Davis P, Kenny E, Kishore R, Lawson D, Lee R, Muller H, Nakamura C, Pai S, Ozersky P, Petcherski A, Rogers A, Sabo A, Schwarz EM, Van Auken K, Wang Q, Durbin R, Spieth J, Sternberg PW, Stein LD: Wormbase: A comprehensive data resource for Caenorhabditis biology and genomics. Nucleic Acids Res 2005, 33(1):383-389.

The cited paper simply describes the WormBase database and includes only a passing reference to the fact that WormBase contains some links to protein structures (when known), but that's about it. The WormBase paper doesn't mention 'folding' or 'classification' anywhere, which makes it seem a really odd choice of paper to be cited. It makes me wonder how many other papers end up gaining seemingly spurious citations like this one.

Thoughts on the supply of bioinformatics services and training in the UK

I am currently at the 2014 UK Genome Sciences meeting (hashtag #UKGS2014). It has been a long time since I have been at a UK science conference and it has been good to meet old colleagues and acquaintances who I have known from various stages of my career.

From informal chats with various people, it seems that UK universities are tackling their bioinformatics needs in different ways. Some have specialized facilities that try to meet the bioinformatics need from local users (and potentially from those further afield). E.g. the University of Surrey has a Bioinformatics Core Facility, Newcastle University has a Bioinformatics Support Unit, and here at Oxford there is the Computational Biology Research Group.

These examples represent core facilities with dedicated staff. An alternative approach is to bring together — physically or virtually — existing bioinformatics talent, with a view that they will be able to help others. This is the strategy taken by the new Bioinformatics Hub at the University of Sheffield, which brings together six talented folk who are based in different departments. The success of strategies like this may heavily depend on having enough skilled bioinformatics faculty who also have enough time to help others.

Other universities seem to lack any central pooling of bioinformatics expertise, and instead rely on people doing bioinformatics themselves or outsourcing it to places like TGAC. The former approach (doing it yourself) will be fine for some people, particularly those who are comfortable learning new computational skills themselves, but this will not be a good fit for everyone. 

If you are not outsourcing your bioinformatics and you don't have the necessary skills yourself, then the other approach is to attend one or more training courses. Three places that seem to be leading the field for bioinformatics training are TGAC, CGAT, and Edinburgh Genomics…and all three have a heavy presence at this conference.

Depending on your definition, bioinformatics has been around — as either a recognized skill set, or a field of study — since the early 1990s. The number of people who might consider themselves a bioinformatician has probably grown exponentially since then. Likewise, the demand for skilled bioinformaticians, or for facilities that offer bioinformatics services and training, continues to grow. Clearly, there are different ways of meeting this demand.

The current diversity of approaches to bioinformatics services and training presumably is a reflection on the local supply of, and demand for, such services. If you are about to join a new university, and if you plan on needing some bioinformatics help at some point, it may be useful to first find out more about that university's bioinformatics strategy.

My poster for the UK Genome Sciences meeting is about a new version of our IMEter software

One of the many projects I am involved with looks at Intron-mediated enhancement (IME) of gene expression. Our collaboration with Alan Rose at UC Davis has been a fruitful one, and has led to the development of computational tools that can predict how much an intron might enhance expression.

The initial version of what we called 'the IMEter' was published in 2008 and an improved v2.0 version was published in 2011. The online version of this software only lets you test Arabidopsis introns…not so useful when there are now so many different sequenced plant genomes.

We addressed this limitation in a new — as yet unpublished — v2.1 version which is available online. IMEter v2.1 can now test the expression enhancing ability of introns from 34 different plant species.

The new IMEter is the subject of my poster at the forthcoming UK Genome Sciences meeting in Oxford. The poster, available below via Figshare, explains a little more about how the new version of the IMEter came about. It also discusses some of the problems that arise in trying to adapt a software tool from working with one, very well annotated, genome, to working with many different genomes of varying quality.