If you’ve been in science long enough, eventually you’ll have reached a point where you needed a safety project, either for yourself or for a student. A safety project is a project whose success is all but guaranteed, that doesn’t require much in terms of critical thinking or properly aligned stars. All that is required to complete a safety project is proper execution of the work.Read More
This week, I finally took the time to clean up the code for my cowplot R package and submit it to CRAN. While the code had been up on github for a while, and I had blogged about it previously, nobody had really taken notice as far as I can tell. However, this time, with an official release and better documentation, people seem to like it a lot. The response on Twitter was overwhelming.Read More
PLOS Biology recently published a nice article on data visualization:
Weissgerber TL, Milic NM, Winham SJ, Garovic VD (2015) Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm. PLOS Biol 13(4): e1002128. doi:10.1371/journal.pbio.1002128
It argues that we can do better than showing data as bars of mean height with error bars indicating standard deviations. In my lab, we use many of the proposed techniques already, see e.g. Fig. 4 in this paper. However, I'm glad that I now have a simple reference I can point people to when I want them to reconsider their figures.
PLOS ONE just published an article providing a cost-benefit analysis of grant writing:
von Hippel T, von Hippel C (2015) To Apply or Not to Apply: A Survey Analysis of Grant Writing Costs and Benefits. PLoS ONE 10(3): e0118494.
One of the main take-home messages: If you write more grants you will get more funding. Also, at current funding rates, unless you're writing 2-3 proposals a year, you have a reasonable chance of going unfunded over a three-year period. The authors suggest that investigators should avoid programs with funding rates at 20% or less unless they are willing to write multiple proposals a year and/or have a particularly compelling research program. However, in biology practically all funding rates are 20% or less these days, so that advice isn't very helpful. Instead, we just need to keep writing proposals. If you're after NIH funding, you should probably write at least one proposal per cycle, unless you've been recently funded. If you're primarily after NSF funding, with yearly cycles, you'll have to diversify and find at least two programs to which you can send your proposals.
This semester, I'm teaching a new introductory class in computational biology and bioinformatics. The class is primarily targeted at undergraduates, and it is split approximately 50:50 between R and python. The R component emphasizes effective data analysis and visualization, using packages such as ggplot2 and dplyr. The python component will introduce students to basic programming concepts, and it will also cover some typical bioinformatics applications.
Developing a new class is a lot of work, so I'll probably have much less time for posting here on my blog. However, on the flip side, the entire course content will be posted online, and you can follow along here. The core of each lecture is an in-class exercise worksheet, and I'm posting the worksheets and the solutions online. Many lectures also have a brief traditional lecture component with slides as well as additional reading materials. I'm developing the course as I go, so there will be new material posted twice a week throughout the spring.
There was a lively discussion on Twitter the other day regarding what constitutes a citable piece of scientific work. In particular, Matthew Hahn was concerned about where to draw the line, and he felt that unless something is traditionally published there’s no need to cite it. When reading this dicussion, I felt it was muddled by the lack of clear criteria separating citable works from other forms of scientific communication. In my mind, there is a clear distinction between preprints, which I consider to be citable works, and presentation slides or tweets, which are not. To formalize this distinction, I would like to propose four conditions that need to be satisfied for a document to be considered a citable piece of scientific work. The document needs to be: (i) uniquely and unambiguously citable; (ii) available in perpetuity, in unchanged form; (iii) accessible to the public; (iv) self-contained and complete.Read More
PLOS ONE just published a paper comparing MS Word with LaTeX, which argues that LaTeX has little benefits over MS Word and should not be allowed by scientific journals:
Knauff M, Nejasmic J (2014) An Efficiency Comparison of Document Preparation Systems Used in Academic Research and Development. PLoS ONE 9(12): e115069.
In my mind, this paper makes extremely strong claims based on a rather flawed and thin analysis. I am sure there are useful things to be said about MS Word vs. LaTeX. However, this paper does not make much of a contribution to this question.Read More
In my previous post on how to prepare an article for resubmission, I failed to mention one important point: In your response to the reviewers, quote the entire referee report, even the introductory sentences. Don’t just quote the specific comments to which you are replying. This may seem unnecessary but it is in fact crucial, in particular if the introductory sentences were largely positive. (If they were highly critical, you may want to omit them, even though in this case you probably should provide a response.)Read More
I came across an interesting paper* that derives a mathematical relationship between the total number of citations a scientist has received, Ntot, and the scientist’s h index**. The paper, written by Alexander Yong, argues that for typical scientists, h is given simply as 0.54 times the square-root of Ntot. The paper also derives confidence bounds on this estimate, and it shows that scientists who have written only a few highly-cited works will generally fall below this estimate. While the paper is set up as a critique of the h index, I think it shows that the h index works largely as intended. It measures the total amount of citations a researcher has received, but it adequately down-weighs the effect of a few extremely highly cited works in a researcher’s publication list.Read More