About planning (or not) your future

I have been quiet for some time, but I will try to post a bit more frequently in the future. This time my post does not have any direct link to plant biology. After watching this video a couple of days ago I was nicely surprised to learn how lucky I have been. Although I am a rather extreme case of a person having many different interests, I have very rarely felt the pressure described by the speaker. In fact many times I have felt encouraged. This may have to do with a different cultural attitude in Argentina, and in addition, because I have almost always connected all those different interests. So, what are those interests? I have training as a crop breeder, but I did find very interesting plant eco-physiology, genetics, micro-meteorology, statistics, systems analysis, computer programming, electronics, photography, and graphics/book design. This seems too much! Doesn’t it? Surprisingly I am using all those skills and interests in my current research and teaching. I did my first experiment with plants, as an undergrad, around 1978 and quite soon after that I designed and built my first measuring instrument, an auxanometer (an electronic instrument to measure plant growth rate with a very good time resolution, of minutes, if not seconds). For this I used what I had learnt of electronics, mostly as a  hobby, and from a friend who studied telecommunications at a technical high school. Then we got the first computer in the lab, an Apple II. Money was scarce, and we had a commercial statistical software that was so awkward to use that I do not think a young person nowadays could imagine that anybody would ever write a program, and be able to charge money for it, where you had to type-in the numbers to analyze one by one, and had no provision for editing any data value after you had entered it. In other words, if you made a mistake, you had type-in again your whole data set! I was not happy with that, so I just wrote a programme myself for ANOVA and ANCOVA. Combining what I had learnt of statistics in regular university courses with what I had learnt about programming mostly by myself, again as a hobby.

I hope none of those of you who do have many different interests, is feeling the pressure described by the speaker. If you do, however, stop worrying, and find ways of combining those interests so that you can either use them together, or alternate among them.



The researchers behind ‘the biggest biotech discovery of the century’ found it by accident in DNA Research

[Business Insider] The discovery of the CRISPR genome-editing technology shows why basic research is so important.

Source: The researchers behind ‘the biggest biotech discovery of the century’ found it by accident in DNA Research

I am posting this as an example that when doing research one has to broadly think how what one is working on may have useful implications for different problems than those we are aiming to study.

The other point, is that basic research, even if it does not have a known or expected application can have a huge contribution to solving practical problems.

Rigor and Reproducibility

The NIH (USA, National Institutes of Health) has opened a new web site on the subject, which although focused on Biomedical research, provides a good account of current trends and problems, how to overcome them and guidelines that could be easily adapted for the rest of the Biosciences including Plant Science.

Rigor and Reproducibility

An interview with Prof. Jorge J. Casal

In the interview Jorge has several insights about his career path and also advice for early stage researchers. I have been Jorge’s friend and collaborator for more than 30 years, and been a witness of how he has followed since he was an undergraduate the path he now gives as advice in the interview. The result has been a successful career doing very original research. (The article is not open-access, so the link will give you free access to the article only through the university network.)

An article in Nature Tools on the “rise of R”

It is nice that R is so popular nowadays. I have been using it since 1999 or so, when Jaakko Heinonen introduced me to it, and been convinced since 2002 when I started teaching it to undergrads, that once one grasps the logic behind it, it is not difficult to use. At that time, I even developed a couple of simple packages for use in my courses. More recently, in the last three years I have been doing a lot of programming in R, as I am developing a suite of packages, while earlier I had been mostly writing simple scripts for analysing data.

R is as a programming language quite unusual and takes some time to learn to squeeze all the possibilities out of it, both in terms of performance and programming paradigms, but I have grown to like it a lot.

A very simple and a bit superficial note on R was published a couple of weeks ago in Nature. The citations record used, surely underestimates the use of R, especially early on, as it was frequent to not cite R as a publication, and least to have the “R project” as the ‘author’ but instead to mention it as a “product” in materials and methods, or to cite the paper “Ihaka R, Gentleman R. 1996. R: a language for data analysis and graphics. Journal of Computational and Graphical Statistics 5: 299–314.” In those times, even some editors refused to accept R itself as an entry in the list of references, something that did happen to me when I submitted a manuscript. The first article I published which cites R, or rather the 1996 paper on R, is from 2001, so although the first references to the “R project” may be from 2003 as mentioned in the Nature article, citations to books and articles describing R and R packages, appeared in the literature already in the late 1990’s.