Tuesday, 23 August 2016

Methodological sabotage of growth rates

Following the interest in a previous post about analysing growth curves in Matlab I would like to discuss issues in growth curves that can arise from the methodological/biological side of things. Fitting the data is perfect if the data is perfect, if not, looking at what is wrong by eye is warranted for future corrections.

Growth curves can be divided into phases (lag, exponential, stationary and death) and each has its pitfalls.

Tuesday, 9 August 2016

Cysteine racemase: an impossible enzyme?

Cysteine racemase is an enzyme (EC that was characterised in lysates long ago, but have never been found since. Is it a real enzyme? Can the reaction happen well? The problem is that racemising via a carbanion intermediate something with a leaving group is not an easy feat.

Friday, 27 May 2016

The witchcraft of knockouts

Making knockouts has a bad rep, but there seems to be a conspiracy afoot to make it feel like a mystic art.

Tuesday, 17 May 2016

Restriction cloning nostalgia

Today I was reminded of an invaluable table that was hung on the wall of every lab: the NEB buffer compatibility chart.

My favorite buffer is buffer 4.

Friday, 13 May 2016

Gene symbol poetry

A rather angry pathway.
"Regulatory protein for 2-phenylethylamine catabolism · two component sensor histidine kinase,essential for acid-tolerance · nikkomycin biosynthesis protein · galacturonide ABC transporter ATPase".
That is my first (and last) attempt at genetic constrained writing: the genes encoding those protein are feaR actS sanS togA, which is a rubbish sentence that makes somewhat sense.
Constrained writing () is an artistic challenge where one writes with a restricted dictionary, for example, there are no word with the letter e in the book Gadsby. Here I restricted my dictionary to words that are also gene symbols.

Thursday, 7 April 2016

Research vs. glitchy data munging

I apologise, but I could not resist this rant...
I am a big advocate for big data —also it's my job—, however one trend I find disturbing is the frequency of attempts to make automated pipelines to predict how one could make a given compound: in a large amount of cases, doing some reading up is way more efficient. Not to mention, without bugs.

Saturday, 2 April 2016

Going solo on a paper

This month my (first) solo paper comes out, which was a big deal as it is, well, my first solo paper.
The short communications describes the web app Mutanalyst: a good/amazing/best/super online tool to help calculate mutational bias spectra especially with poor sampling —in case you were wondering what does shameless Search Engine Optimisation look like, there goes an example. The topic is straightforward as it describes a web program I wrote with a twist, namely it calculate the standard errors, which are dismal when sampling is limited. The weird part is submitting a paper without backing, hence the account of my saga here.