Peer reviewing and atavisms

Summary: let’s make manuscripts for review reviewer-friendly instead of atavist-editor-friendly.

There are many things we carry on because of … let us call it “tradition” to avoid calling it by its proper name: “atavism.”

Today I am finishing reviewing a manuscript, and I feel irritated again that the article has the figures last, by themselves, and that I have to jump from one page with all the figure legends, while trying to match them to figures that the journal’s software had the good idea to tag with numbers, but still, no legends. Shit. I wonder, I publish articles myself, and I have decided to put the legends at the bottom of the figures because my experience as a reviewer has told me how much easier it would be if this was the norm. A few journals, when you upload figures, have a field for the legend, but few authors seem to notice. What about mes amis et amies, you made this very clear to authors? Why do we carry on with this atavism from much older times when figures were sent by snail mail, for lack of anything better, and pages had to be put physically together, and a whole process of postprodution (I don’t know why the speller is suggesting “prostitution” instead of this word) carried on. Who knows why the figures had to come separated from the legends, but whatever, it was so. Today, we electronically send the figures and manuscript first for review, and we are asked later to send “production” figures anyway. So why not save some pain to our peer reviewers and give them something easier to examine? Shit, even if the journal does not ask you so. They will ask for “proper” figure later anyway (if and when your article gets accepted, that is). So double and triple please, put those legends with the figures. Let us stop this atavist custom and be merrier.

Most sincerely,

Gabo, the angry reviewer

Updated collaborations page

So take a look if you wish to know who we collaborate with. It might still be incomplete. I am trying to have it as complete as possible, but, believe it or not, I collaborate with some people I don’t know. Of course most names are of P.I.s, but the collaborations are supposed to mean the labs of these magnificent people too.

New members of the lab

Quick note to give a welcome to our two new members of the lab. Marc del Grande, who started his M.Sc. studies in May, and Aisha ElSherbiny, who starts as a postdoctoral fellow this July.

Marc’s project is about the evolution of regulons, while Aisha will be involved in analyses of high-throughput experiments on transcription factor binding sites (operators), DNA signatures, and much more.

Computational Genomics and Metagenomics


Network of functional interactions for the arginine repressor

Welcome to the web page of the lab of Computational Genomics and Metagenomics, a.k.a. the lab of Computational Microbiology, the lab of Computational Microbiomics, and the lab of Computational Con-Sequences.

We are interested in all things genomic, metagenomic, postgenomic, postmetagenomic, and hyperultramegasupragenomic (!). Our work centres around the evolution and the inference both of function and of functional interactions of gene products, mostly in Prokaryotes.

Everything in this lab is done with computers. Yet, besides working with other computational biologists, we also have collaborations with wet labs.

You might be wondering how this kind of research got started. Well, it all began with the idea that we should stop finding the genes in the human genome, one by one, by laborious and intense work linking phenotypes (what we see) to finding the very gene, or genes (what we don’t see), responsible for such phenotypes. Not that such work is not valuable, au contraire, without that work providing us with real life examples we would not be in any position for making sense of genome sequences. It was probably some kind of a case of impatience [and boldness]. Of course, there is also the tiny detail that knowing our complete genetic complement (a useful definition of “genome”) would provide us with a wider and more accessible basis for the better and faster finding of genes behind phenotypes. Now, substitute the word “phenotype” by whatever disease that might involve genetics (or badly gone genetics), such as “cancer,” or “diabetes,” and you might get a better feeling of importance for this task.

As you might guess, quite well, this ambitious project set the whole machinery in motion. Long story short (but I might try and let you know better later), the technological advancements brought about by the idea of having our beautiful 23+1/2 pairs of chromosomes sequenced allowed scientists to sequence microbes. With those genomes available, before we even had a first draft of our own, other technologies arose, technologies focused on making sense of newly found genes in those genomes. A couple of these are transcriptomics, which started with microarrays, used to find out which genes are expressed by finding their messenger RNAs; and proteomics, used to figure out which proteins are being produced. That my friends, started the “postgenomic era.” I gave it away, didn’t I? You have thus guessed that “postgenomics,” in the second paragraph, refers to the products of these new technologies, and you are absolutely right.

Well, not content with the human genome (the draft was announced in 2000, yes, ten years ago!), and with powerful sequencing technologies available, another new field arose. The field of environmental genomics, or metagenomics (the word “metagenomics” was used to mean the fishing of genes with particular functions from the environment, before it was used in this context, but let’s not go there). This thing is about sequencing fragments of DNA isolated from an environment (I was going to write “from a given environment,” but I resisted), and then guessing things about the microbes, or whatever, in such an environment. Others refer to “metagenomics” as sequencing without culturing, but let’s not go there either. Well, since now scientists are sequencing mRNA, rather than DNA, we could say that the postmetagenomic era has dawned. Though I haven’t seen this word used in a paper yet. In any event, such a humongous amount of data necessarily calls for computational analyses, and here we are.

Well, hard to guess where all this is going, but the sequencing technologies keep improving and getting cheaper. We cannot but expect the word “deluge” in all of the published papers of the genomic era to become ridiculous by comparison. This means lots of challenges to make sense of the information. Lots of new avenues of research too. This is why I am reserving the word “hyperultramegasupragenomic” (and its “post-” derivative) for later use. The way things are going, it might not be that much later.

With that, welcome again, and enjoy your visit.


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