30 years of Art meeting Science. A lecture by William Latham.

Leopard jacket, a plastic red shirt. A kitsch style that only Brits can wear with unquestionable style. William Latham gains the attention at the first sight. Born in 1961, he pioneered the field of computer art, and got known for his organic artworks based on the processes of evolution. After having founded the Computer Artworks Ltd, game studio that produced the horror videogame “THE THING“, he joined the Goldsmith University of London for a Computer Art professorship. Being involved in a research project where he applies his evolutionary rule-based approach to the domain of protein folding, there is definetly no one better than him to explain the encounter of art and science in the last 30 years.

If you have an hour and half free, you can consider chilling with this amazing lecture, where prof.Latham will go explain the merge of art and science in several fields, such as architecture, dance, rave culture, genetics, creative development in video game and neurosciences.


Metagenomics: exploring the Phyloseq package

Sometimes, I wonder if our limited ability to cultivate bacterial species represented an advantage. In fact, this lack has boosted the development of methods for the analysis of environmental samples, and the question is what would have happened if we had the chance to grow each species, would we have been able to understand the complexity of microbial communities, their emergent features and the importance of an holistic approach?

Tough question, and I fear that this post would be too long to fulfill a proper dissertation, that is a matter on how methods development drives the way we do science, and vice versa. In the meanwhile, as many out there are enjoying the challenging benefits of holistic approaches in microbiology, let’s have a look on what’s going on in the development of a rapidly growing project for data analysis in metagenomics: the Phlyoseq project.

Published by Paul J. McMurdie and Susan Holmes at Stanford University in 2013, Phyloseq is an object- oriented R package, designed to ease the life of anyone dealing with analysis of microbiome census data. Those analysis can be made by several techniques, and a variety of file formats are thus generated. That is why the authors underline the importance of reproducible research, often reported to be quite rare in microbiome census data, and provide some example of reproducible protocols.

The workflow displaying down here, illustrates the functioning of Phyoloseq. As shown, OTU clustering and independently- measured sample data are accepted as input, pre- processed and submitted to analytic procedures available in R for inference and validation. Rounded rectangles and diamond shapes represent functions and data objects respectively.


Some days ago, the Phyloseq team published a new package, an interactive web application that provides a graphical user interface to analyze Phyloseq data. As the name suggests, Shiny- Phyloseq is developed within the Shiny framework, a R- dedicated web framework. This front- end interface complete the back- end Phyloseq implementation, providing a comprehensive and easy-to-use software for genome scientists working on microbiome.

Further information, tutorial and downloads are to be found on GitHub.

Phyloseq on GitHub.io

Shiny Phyloseq on Github.io


Researchers get *shot* in Italy as #ScienceBulletChallenge goes viral.

#ScienceBulletChallenge is a viral initiative aimed at reporting the untenable labor conditions of scientists in Italian public research centres. A recent investigation claims that, in the last decade, the 93,3% of italian Science personnel was hired according to the so- called “precarious employment contracts”. In Italy, we use the term “precarious” (precario) to indicate those employment contracts that are limited in time, and usually payed with a monthly income ranging around 1000 euros. When I say “limited in time”, I am pretty serious about the definition of “limited”. Many contracts last one year, but you will often get to talk with people having a stipend guaranteed for few months only. Also, the dramatic rise of inflation in recent times has meant that you just cannot live in a big city with 1000 Euros per month.

The worst part is that there is a dramatic consequence on researchers’ private life. The same investigation states that the 74% of the population sample considered has no children, although the mean age is 35. You cannot really ponder to have a family when you are not even sure of your fate in coming months. Many very advanced research centers in Europe are giving a lot of importance to the quality of life of their employees, because Science activity needs creativity to be productive, and creativity needs a good overall quality of life to be expressed. You can only imagine how much this situation is affecting Science production in Italy.

Anyways, maybe not everything is lost in terms of creativity here, as this #ScienceBulletChallenge witnesses. The deal is quite simple: as in the world-famous “ice bucket challenge”, you are dared to publish a video on social media. No ice bucket, but a “bullet” of choice. The challenged will get shot by a fictional weapon to show how researchers are “shot” and polished off everyday by the insane italian policy on public research. If you are adventurous enough to deal with Italian language, you may browse the official website. The initiative has been contrived and promoted by three anonymous researchers from Sapienza University in Rome.

Hey scientists, chill down and "watch" some music.

Find awesomeness and let it trill you. Art, music and any good fuel for your brain is very needed in Science, because we constantly need to bring our mind higher, and very often far away from pur books, papers, pwerpoints, experiments and scripts. Otherwise, terrible things may happen. So, if you are bored, tired, pissed with your boss, or just fed up with this fucking Horizon2020 application round, you may consider unfasting your belt, put headphones on and chill down with classical music. The Musanim project is aimed to develop a visualization system for music. Any sound channel, any instrument, is visualized as an unique stream of images. The composition is an amazing flow of images and graphs that will let you actually see the music you listen.

Here, I post one of my favorite movements, the Pachelbel’s Canon in D- second movement, but the official Musanim youtube channel will display tens of notable classical tracks.

Chill out, funding will come 🙂

Bioconductor goes cube. Welcome to Bioconductor 3.0

Right about now, the bioconductor team announced the release of Bioconductor 3.0. The release consists of 934 software packages, 219 experiment data packages, and 870 up-to-date annotation packages. Many packages have been updated and improved, and the new version will come out  with 114 new software packages.


Scrolling down the list of new software included in this release, NGS analysis and whole systems analysis tools account for the majority, confirming how they are the hot topics in current research.

More comments will come in the next days, as long as the new version will be tried out. In the meanwhile, you can download and install it from here. Bioconductor 3.0 is compatible with R 3.1.1 and available for MacOS, Windows and Linux.

For all those are moving their first steps in bioconductor, a very extensive and straightforward guide is available on this free tutorial released by the University of California- Riverside.

The Oncodrive suite. Bionformatics methods to detect driver mutations in cancer.

One of the most amazing groups whose work I have recently explored, is based in the rapidly- growing young UPF university in Barcelona. The Biomedical Genomics Group applies its high computational expertise to cancer research, focusing on the identification of those mutations that are actually involved in determining the tumor phenotype, the so- called driver mutations. The tool I share with you today is aimed at the identification of driver mutations using a clustering approach. The idea is quite simple: since gain of function mutations in cancer use to cluster in specific protein regions, thus providing an adaptive advantage to cancer cells, one can use this feature to identify a driver mutation. This is a crucial need for anyone working in cancer genomics. As you sequence the genome of a cancer cell, you basically find a total mess of mutations, and your job is to distinguish the ones that determine cancer.

One of the current challenges of oncogenomics is to distinguish the genomic alterations that are involved in tumourigenesis (i.e. drivers), from those that give no advantage to cancer cells, but occur stochastically as a by-product of cancer development. (Bioinformatics, 2013)

The lab published a set of tools, actually a real software suite called Oncodrive, to provide a computational method to the identification of cancer mutations. On august the 27th 2014, the group announced the publication of a new member of this suite: OncodriveROLE, and I take this to publish a short resume of the whole suite.




Method to identify cancer drivers from cancer somatic mutations in a cohort of tumors. It computes the bias towards the accumulation of variants with high functional impact (FM bias).

link | paper


Method to identify genes that accumulate copy number alterations important for tumour development. This is done by computing the functional impact of CNAs by measuring their effect on the expression of the genes affected.

link | paper


Method to identify genes in which mutations accumulate within specific regions of the protein, which denote events selected by the tumour. It computes a score measuring the mutation clustering of a gene across the protein sequence and compares it with a background model.

link | paper


Method to classify cancer driver genes into to Activating or Loss of Function roles.

link | paper

I haven’t tried them since I am working on dystrophy and still have no mutations to detect, but if I got this straight, all the scripts come out as python libraries. Moreover, I really suggest you to visit the lab’s page for tools to find out up to 13 different cancer- dedicated software solutions available for the use.