The Tesla index: a measure of social isolation for scientists

Abstract

In the era of social media there are now many different ways that a scientist can build their public profile; the publication of high-quality scientific papers being just one. While publishing journal and book articles is a valuable tool for the dissemination of knowledge, there is a danger that scientists become isolated, and remain disconnected from reality, sitting alone in their ivory towers. Such reclusiveness has been long been all too common among academic scientists and we are losing sight of other key outreach efforts such as the use of social media as a tool for communicating science. To help quantify this problem of social isolation, I propose the ‘Tesla Index’, a measure of the discrepancy between the somewhat stuffy, outdated practice of generating peer-reviewed publications and the growing trend of vibrant, dynamic engagement with other scientists and the general public through use of social media.

Introduction

There are many scientists who actively take the time to pursue their science in as much of a public manner as possible. They work hard to ensure that their peers, and the public at large, are kept informed of their latest research. Consider Titus Brown, a genomics and evolution professor at Michigan State University[1]. Although he has contributed to a meagre number of — largely uninteresting — publications[2], he has instead embraced social media[3] to excite and stimulate others with news of his past, current, and future work.

Now consider Nikola Tesla[4]; although he may have forever changed the world through his many scientific inventions[5], he was a famous recluse[6] and surprisingly did not contribute to any blog, nor did he even bother to set up an account on twitter. I am concerned that the anti-social and secretive behavior of Nikola Tesla is something that is all too common in many other scientists, particularly in those who continue their obsession with publishing work that will forever live behind pay-walls, invisible to all but the priviledged few.

I therefore think it’s time that we develop a metric that will clearly indicate if a scientist is a reclusive introvert with no interest in sharing their work with others or engaging with the wider community. This will allow others to adjust our expectations of them accordingly. In order to quantify the problem and to devise a solution, I have compared the numbers of followers that research scientists have on twitter with the number of citations they have for their peer-reviewed work. This analysis has identified clear outliers, or ‘Teslas’, within the scientific community. I propose a new metric, which I call the ‘Tesla Index’, which allows a simple quantification as to the degree of social isolation of any particular scientist.

Results and Discussion

I took the number of Twitter followers as a measure of ‘social outreach and engagement’ while the number of citations was taken as a measure of ‘boring scientific output’. The data gathered are shown in Figure 1.

Figure 1: Twitter followers versus number of scientific citations for a sort-of-random sample of researcher tweeters

I propose that the Tesla Index (T-index) can be calculated as simply the number of Twitter followers a user has, divided by their total number of citations. A low T-index is a warning to the community that researcher 'X' may be forsaking all methods of publicly sharing their work at the expense of soley publishing manuscripts. In contrast, a very high T-index suggests that a scientist is being active in the community, informing and educating their peers, colleagues, and the wider public. They are thus playing a positive role in society. Here, I propose that those people whose T-index is lower than 0.5 can be considered ‘Science Teslas’; these individuals are highlighted in Figure 1.

References

  1. http://ged.msu.edu  ↩

  2. http://scholar.google.com/citations?user=O4rYanMAAAAJ&hl=en  ↩

  3. https://twitter.com/ctitusbrown  ↩

  4. http://en.wikipedia.org/wiki/Nikola_Tesla#Literary_works  ↩

  5. http://theoatmeal.com/comics/tesla  ↩

  6. http://www.viewzone.com/tesla.html  ↩

Acknowledgments

This research was inspired by a piece of completely unrelated work by Neil Hall. 

Ewan Birney's EBI press conference on being elected to the Royal Society

Speaker: And that concludes this EBI press conference to congratulate Ewan Birney on being elected to the Royal Society. We just have time for one or two questions. Ah okay...the first question goes to…Ewan Birney.

Ewan: Hi Ewan. Just wanted to say that this is all great and I've found your work to be really interesting. Can I just ask whether you've looked at the opportunity of widening this effort by joining other Royal Societies as well? This would allow for a much better comparative analysis of the scope and impact of Royal Society members? The Royal Statistical Society may be a good choice to begin with, or maybe the Royal Society of Marine Artists.

Ewan: Thanks Ewan, that's a really good question. It is something that I'm considering and I think there is a lot to gain from such a comparative approach. But to do this properly I think it needs to be part of a much larger effort. So I'm hopeful of trying to join every Royal Society and then see what can be learned from a cross-societal analysis of such memberships. Furthermore I'm hopeful that Her Majesty could be persuaded to start a new Royal Society for the Promotion of Questions by People Named Ewan at Academic Conferences…something that is very near and dear to my heart.

Speaker: Okay, I think we have time for just one more question. Oh, Ewan…again.

Ewan: Just to follow up Ewan, given the advanced age of many Royal Society members, have you thought about trying to assess what fraction of the Royal Society is functional?

Ewan: That's a fantastic question Ewan, very perceptive of you. This is something else that I have a strong interest in. I am currently involved in some preliminary discussions with various people to form a new pan-European working group that will investigate how much of the Royal Society is functional. This effort will hopefully be called ENCODEMBLIXIR…or something snappy like that. 

 

Jesting aside, congratulations Ewan this is great news!

An 18 Kbp read from a MinION sequencer!

The UC Davis Genome Center was fortunate to receive a few MinIONs from Oxford Nanopore the other week:

One of the things that we have been trying to do with these wondrous machines is to study variation in a mixed pan-European population. For this study, we simply combined saliva samples from individuals that represent 32 distinct European ethnicities (but no Belgiums, obviously), and the combined sample was applied directly to the MinION using the WF10 setting (WF = warp factor).

The preliminary results look very promising with an N50 read length of 12.2 Kbp (and this was before applying N50 Booster!!!). Here is the very first read from the device...18,731 bp of pan-European goodness (though note that there was a problem with base quality at the end of the read...contamination with Belgium DNA maybe?).

>PanEuroMix_read00001 

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A new tool to boost the N50 length of your genome assembly

We all know that the most important aspect of any genome assembly is the N50 length of its contigs or scaffolds. Higher N50 lengths are clearly correlated with increases in assembly quality and any good bioinformatician should be looking to maximize the N50 length of any assembly they are making.

I am therefore pleased that I can today announce the release of a new software tool, N50 Booster!!! that can help you increase the N50 length of an existing assembly. This tool was written in C for maximum computational efficiency and then reverse engineered into Perl for maximum obfuscation.

This powerful software is available as a Perl script (n50_booster.pl) that can be downloaded from our lab's website. The only requirement for this script is the FAlite.pm Perl module (also available from our lab's website).

Before I explain how this script works to boost an assembly's N50 length, I will show a real-world example. I ran the script on release WS230 of the Caenorhabditis japonica genome assembly:

$ n50_booster.pl c_japonica.WS230.genomic.fa

Before:
==============
Total assembly size = 166256191 bp
N50 length = 94149 bp

Boosting N50...please wait

After:
==============
Total assembly size = 166256191 bp
N50 length = 104766 bp

Improvement in N50 length = 10617 bp

See file c_japonica.WS230.genomic.fa.n50 for your new (and improved) assembly

As you can see, N50 Booster!!! not only makes a substantial increase to the N50 length of the C. japonica assembly, it does so while preserving the assembly size. No other post-assembly manipulation tool boasts this feature!

The n50_booster.pl script works by creating a new FASTA file based on the original (but which includes a .n50 suffix) and ensures that the new file has an increased N50 length. The exact mechanism by which N50 Booster!!! works will be evident from an inspection of the code.

I am confident that N50 Booster!!! can give your genome assembly a much needed boost and the resultant increase in N50 length will lead to a much superior assembly which will increase your chances of a publication in a top-tier journal such as the International Journal of Genome Assembly or even the Journal of International Genome Assembly.

Update: 2014-04-08 09.44 — I wrote a follow up post to this one which goes into more detail about how N50 Booster!!! works and discusses what people could (and should) do to the shortest sequences in their genome assemblies.