syncopation & accordionlike France, but no dog poop

# science: exciting

Workshop at Brain and Mind Symposium, Långvik Congress Center, Kirkkonummi, Sep 17–18 2015.

# EMBO Journal 2011 Cover Contest

## non-scientific image entry - fiber optics - honourable mention

For the EMBO Journal 2011 Cover Contest, I prepared two entries, one for the scientific category and one for the non-scientific category.

The non-scientific entry is abstract photo of fiber optics. The scientific entry was an information graphic showing a hive panel of genomic annotations in human, mouse and dog genomes. The hive panel is based on the use of the newly introduced hive plot.

## About the EMBO Journal Cover Contest

The EMBO Journal non-scientific cover prize is awarded for the most interesting and beautiful image made outside the lab. Contestants may submit, for example, photos or artistic impressions of wildlife animals, plants or landscapes. Particularly welcome will also be hand or computer-generated paintings or drawings (or photographs of other works of art) related to a biological or molecular biological topic.

The EMBO Journal scientific cover prize is awarded for the most captivating and thought-provoking contribution depicting a piece of molecular biology research. Entries can include light or electron micrographs, 3D reconstructions or models of biological specimen or molecules, spectacular artefacts collected in the lab, original new views of lab equipment (but not of colleagues!), or other research-based images to be of interest to molecular biologists.

Examples of scientific cover image winners from previous years. My Circos image (top left) won the 2010 scientfic image cover category. (see more)

## 2011 Contest and Image Status

The 2011 winners have been announced. The scientific image winner was Heiti Paves, who submitted a confocal image of an Arabidopsis thaliana anther filled with pollen grains. The non-scientific winner was Dieter Lampl, with his "Blue Ice" photo — a glacier in Los Glaciares National Park in Patagonia.

My non-scientific entry (photo of fiber optics) received honourable mention and was included in the Favourites of the Jury gallery.

## non-scientific image entry - fiber Optics

Four genomes — The illustration, originally part of a poster, shows syntenic relationships between human, chimpanzee, mouse and zebrafish genomes. Curved links encode sequence similarity and outer data tracks represent consensus similarity statistics and orthologous genes. The cover image shows a detail of a visualization prepared with the free genome comparison tool, Circos. (EMBO Journal - Best Scientific Cover - 2010)
My 2011 non-scientific fiber optic entry appears in a gallery of a small selection of images that were shortlisted by the jury of The EMBO Journal Cover Contest 2011. Images were selected with the aim of highlighting the diversity and quality of submissions in both, the scientific and non-scientific categories of the contest. (view gallery)

My non-scientific entry was an abstract image photo of fiber optics. It received honourable mention and were included in the Favourites of the Jury gallery.

The motivation and technical details behind these photos are described here.

The other entry, a scientific image, was an information graphic showing a hive panel of genomic annotations in human, mouse and dog genomes, based on the use of the newly introduced hive plot.

My submission of a large Circos figure for its cover (see right), which was originally designed for a poster that introduced Circos, was awarded the 2010 EMBO Journal best scientific cover prize.

## entry details

Some time ago, I did a personal project of photos of fiber optic strands. These worked out well. I had not done anything with these images, and thought they would make a competitive entry into the cover contest.

My first attempt at photographing fiber optic lamp strands. These images were bundled into a set called Diving Horror, because of their likeness to creepy tentacles of creatures of the deep. (more images on flickr.)

I revisited the fiber optic lamp with a higher resolution camera (Canon 5D — original images were from a Canon 20D) and a dedicated macro lens (Sigma 150mm f2.8 EX APO DG HSM Macro) (original images were shot with the Canon EF 24-70L).

From these new images, shown below, I created five EMBO Journal cover submissions.

Second attempt at photographing fiber optic lamp strands. (more images on flickr.)

The submissions would render on the cover as shown below.

Photos of fiber optic lamp strands. (More images on flickr.)

## 2011 EMBO Journal cover contest — fiber optic lamp submission images

2011 EMBO Cover contest submission — macro photograph of fiber optic lamp strands. (More images on flickr.)

2011 EMBO Cover contest submission — macro photograph of fiber optic lamp strands. (More images on flickr.)

2011 EMBO Cover contest submission — macro photograph of fiber optic lamp strands. (More images on flickr.)

2011 EMBO Cover contest submission — macro photograph of fiber optic lamp strands. (More images on flickr.)

2011 EMBO Cover contest submission — macro photograph of fiber optic lamp strands. (More images on flickr.)

# Bayesian statistics

Thu 30-04-2015

Building on last month's column about Bayes' Theorem, we introduce Bayesian inference and contrast it to frequentist inference.

Given a hypothesis and a model, the frequentist calculates the probability of different data generated by the model, P(data|model). When this probability to obtain the observed data from the model is small (e.g. alpha = 0.05), the frequentist rejects the hypothesis.

Nature Methods Points of Significance column: Bayesian Statistics. (read)

In contrast, the Bayesian makes direct probability statements about the model by calculating P(model|data). In other words, given the observed data, the probability that the model is correct. With this approach it is possible to relate the probability of different models to identify one that is most compatible with the data.

The Bayesian approach is actually more intuitive. From the frequentist point of view, the probability used to assess the veracity of a hypothesis, P(data|model), commonly referred to as the P value, does not help us determine the probability that the model is correct. In fact, the P value is commonly misinterpreted as the probability that the hypothesis is right. This is the so-called "prosecutor's fallacy", which confuses the two conditional probabilities P(data|model) for P(model|data). It is the latter quantity that is more directly useful and calculated by the Bayesian.

Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of Significance: Bayes' Theorem Nature Methods 12:277-278.

Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of Significance: Bayes' Theorem Nature Methods 12:277-278.

# Bayes' Theorem

Wed 22-04-2015

In our first column on Bayesian statistics, we introduce conditional probabilities and Bayes' theorem

P(B|A) = P(A|B) × P(B) / P(A)

This relationship between conditional probabilities P(B|A) and P(A|B) is central in Bayesian statistics. We illustrate how Bayes' theorem can be used to quickly calculate useful probabilities that are more difficult to conceptualize within a frequentist framework.

Nature Methods Points of Significance column: Bayes' Theorem. (read)

Using Bayes' theorem, we can incorporate our beliefs and prior experience about a system and update it when data are collected.

Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of Significance: Bayes' Theorem Nature Methods 12:277-278.