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Last week we hosted the visit of G.Scardoni, the author of Centiscape, a Cytoscape plugin to calculate different measures for Node Centralities in a network.

I recommend you to read the supplementary material 1 of his paper (it’s a pdf), because it has a good description of many measures of node centralities and their possible explication in a biological context.

A node centrality is a parameter that, given a node’s position and interactions in a network, determine its importance. To understand it better, think that one of the main purposes of centralities for biology is to identify which genes are more important in a biological process: which are in a bottleneck position, which are required for having a proper function and which ones are only redundant.

The simplest measure of node centrality is the Degree, which is the number of connections of a node. It seems logic to think that genes with an higher degree (higher number of interactions) should be more important than the others, because a loss of function there will affect more interactions. However, after reading at the Centiscape plugin I realized that there are a lot of measures for node centralities, including closeness, betweenness, stress, centroid, etc. The degree is not the best parameter to identify genes in bottleneck positions, for which we should use betweenness or stress instead.

Just to make this post round, I have opened a discussion on biostar about which measures of Node Centrality can be applied to biological networks. Let’s see what comes out from that discussion, and if there are other centralities I do not know yet :-).

Apps and Games

• FreePub is a mind-mapping software to organize scientific materials. Check also this presentation
• After the games about protein folding and multiple alignments, a new geeky bioinformatics game has been published on Internet. Check out EteRNA!

A way to explain what Blast is to young students or non-scientists is to say that ‘Blast is the equivalent of Google for searching sequences‘.

This analogy is controversial and not all the bioinformaticians would agree on it: but it is one of my favorite ways to explain what is Blast to people outside science, and it is the explication I use during Open Days or Science Meets Society events.

In this post I will discuss the Pros and the Cons of explaining Blast as the correspondent of Google for scientists. It is up to you to judge and start using the analogy for your own.

Pros

– Both are for searching.

The most common usage for Blast is to search for a sequence, to see whether it exists or if a similar sequence is already known. In this sense, a Blast query is equivalent to a Google query, where you type a word or a phrase and you want to know what is already known about it.
Let’s say you have the sequence ACGAGGGCATCGATCGACCTATCTCTTTCTAGGCAATC: what would be the first thing to do to know it’s function and role? Just blast it, and see which results come out. Similarly, let’s say that you encounter a phrase you don’t of which know the meaning, like ‘Asparagine N-Glycosylation’: how can you know what does it mean? The easiest solution is just to google the phrase and see what comes out. I think that it is important, for a student, to understand this analogy: Blast can be used to understand what it is known about a  sequence of nucleotides or aminoacid.

– Both are used because they are popular.

What makes of Blast the most used alignment engine, while there are a lot of alternatives available?
The main reason is that Blast is the most popular and well known tool of the genre, so many researchers just use it as the default alternative. Moreover, it is robust and people trust the results it returns, like for Google.
This does not mean that Blast is the best alignment tool for everything: for certain tasks it may be better to try an alternative, as there are alternatives to Google.

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These days I have been having problems with the DNS services, which should have been solved by now.

For approximately one week, this blog has not been reachable from all the world, depending on which DNS servers you were using. Instead, an older version of the site was shown, at least here in Spain and in some parts of Italy.

Everything should be fixed now.. sorry for the inconvenience.

I have opened a new discussion on Biostar, on ‘What is the best question that you have asked, or heard asking, in a bioinformatics seminar?‘

For a scientist, it is very important to be able to make good questions; seminars are a good place to practice. In my case, I am lucky because in the building where I am doing my PhD there are always a lot of seminars, and at least one each week is about bioinformatics.

My favorite question is to ask about the controls that a bioinformatician used to test the software he wrote, or the analysis he did. When I was studying in Bologna, my former professor of Molecular Biology used to repeat us, in almost each lesson, that the most difficult part in designing an experiment is to choose the best controls. I believe that the choice of controls is the moment when a bioinformatician is closer to the biology he/she is studying, because you can’t do that if you don’t know the biology behind your project.

For example, yesterday I attended a seminar from one of the responsible of Ensembl Compara. My question was: which controls do you use when you update the pipeline to predict orthologs? I was wondering whether, with all the experience in predicting orthologs that the Ensembl Compara programmers have, if they know of any gene for which there is so much literature that anyone can be absolutely sure about its orthologs in other species.

So, what is your favorite question to ask in a seminar of bioinformatics? Which controls are you using in your analysis? 🙂