That’s it! Last week I defended my PhD thesis!! I have gone through it, and survived to tell!
I don’t feel very different from before, apart from being relieved :-). Now the future is possibly more difficult than before, because I have to look for a job position and finish a lot of things.
While I was preparing the slideshow, I realized that there are not many examples of presentations for a PhD defence online. This is bad, because you need all forms of help to prepare this presentation.The PhD defence is the last thing that you do as a PhD student, so you want to do it perfectly. It is also the moment when you describe many years of your work to the your colleagues and family. Thus, it is bad that there are few examples of slideshows for PhD defence online.
Here is the presentation that I have prepared for my defence. I hope that it will be useful to other people as an example for their defences.
I think that, for this type of presentation, the first slide to make is the “summary of the talk” slide, like the “Topics” slide I have. Usually I don’t like to have such summary slides in my presentation, but for the Thesis defence it is very important, because it gives you a feeling of security when you present. Having a well defined structure allows you to know when you can stop to drink some water or to check if everybody is following, and to know exactly what to say in each slide of the talk.
In these slides, I did my best to communicate to the students what is philosophy behind the Unix systems and why they have been so important in the past. The Unix philosophy is in reality an approach to data analysis and programming: I am happy if I have been able to convince the students that, by studying how the first programmers have approached the problem of data analysis, they will be able to learn good programming practices, and avoid mistakes that have already been surpassed many years ago.
I would like to thank my colleague Brandon Invergo and my supervisor Hafid Laayouni for suggestions on how to improve the slides. Enjoy!
I gave the second part of the talk on Version Control and hg for my group (check the first part). Here you have the slides:
I am working in collaboration with some of my colleagues to write a pipeline for calculating some tests for our projects.
The idea is to use hg to coordinate the writing of these scripts. We will have a reference version of the scripts on a private bitbucket.org repository; then, everybody will synchronize its local copy of the scripts from there, uploading new changes to the same place.
Some of my colleagues told me that hg is much easier than what they thought. I am very happy of this because I was worried about it being too difficult to use. It is really a long time that I want to convince my colleagues to adopt some version control tools, and it seems that it was easier than what I expected.
These slides are from a talk I gave earlier this week to my lab, describing two papers we published recently:
(slides are published on Nature Precedings: you can vote it here)
Bioinformaticians frequently use data and annotations from scientific databases, like KEGG or Uniprot. However, it is difficult to know how much accurate this data is, and to which extent it can be used for a large scale analysis.
So, the talk is about this. Let’s say you dedicate 6 months of my PhD thesis to accurately study and annotate a set of genes, like I did for the N-Glycosylation pathway: How many errors or unclear annotations do you expect to find in scientific databases?
Another topic discussed in the talk is the issue of how to report an error to a database. Many databases do not have a transparent system to report errors, so any incongruence is correct behind the scene, generating some issues to reproducibility. Moreover, the process of reporting errors to a database is basically not acknowledged by the scientific community, and this is unfortunate because if it were more recognized we could have better annotations in the databases and a more active scientific community.
Dall’Olio GM, Bertranpetit J, & Laayouni H (2010). The annotation and the usage of scientific databases could be improved with public issue tracker software. Database : the journal of biological databases and curation, 2010 PMID: 21186182
Dall’olio GM, Jassal B, Montanucci L, Gagneux P, Bertranpetit J, & Laayouni H (2011). The annotation of the Asparagine N-linked Glycosylation pathway in the Reactome Database. Glycobiology PMID: 21199820