“Virtual brain” site

on Saturday, March 2nd, 2013 4:00 | by

Arnim Jenett (Janelia Farm Research Campus), Kazunori Shinomiya, Kei Ito (both Tokyo University), and other anatomists made a great site with a 3D-viewer of adult Drosophila brains available. You have the chance to scroll threw a whole mount stack while ticking different brain areas. Those brain areas are listed next to the stack. Different areas are coloured differently, so that you can look at the location of several areas in the same brain. On the main page you can find simply explained tutorials about the usage of the site. It is correlated to the anatomical search engine of the Janelia farm GAL4 collection.
Because it was very helpful to me to learn all the synonyms of relevant areas and because I think it is very helpful to learn more about the structure of the Drosophila brain in general I wanted to advertise the site here.

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Science and semantic web

on Friday, January 18th, 2013 7:04 | by

I was on a meetup of corporate semantic web last Tuesday. These people are using semantic web technologies (making machine readable content based on ontological terms and relation between these terms) to improve the efficacy of private companies. For instance, they work on ways to improve wiki contents which may be produced in a company. This corresponds at using ontological term to annotate the wiki content and other related technologies. This can be used to find an expert in one category (=somebody who’s posts are rarely corrected on a specific subject).

What is the scientific community (the one which should be leading the way actually) doing during that time: we use text search in “keywords” and titles to find the appropriate literature, that we have to read thouroughly to drive our one conclusions about these different parts… At least, that is what we do 90% of the time, and we all know how inaccurate this can be. Experimental results may be translated into a machine readable content, why aren’t we doing it (it could make everything that much simpler, faster and more accurate)?

The answer: 1. there is no tool nor database where we could do it. 2. Scientists do not have the time to do it, they are over-pressurized to produce data, not to make it reusable or machine readable.
How to push people to use the semantic web technologies, how to ease this use, should it be done by the authors or by the community, pre or post publication, what ontology tool to use,… What can we do? Is anyone asking these questions around? Does a platform like researchgate be a way to introduce this, or should we go for a public solution, inside pubmed for example?

Is any of you asking/answering these questions?

By the way, this post is tagged by none-ontological terms, a shame?

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Trajectory data: database structure

on Thursday, December 20th, 2012 5:16 | by

CeTrAn is our software to analyse trajectory data, written in R it is free and open source . It was designed to analyse data obtained in the Buridan’s experiment setup. I am now trying to have a larger scope and incorporate different type of data:, for instance:

– Buridan’s experiment done with a different tracker

– Walking honeybee tracking in a rectangular arena, with a rewarded target

– Animal (flies/bees) walking on a ball, using open- or closed-loop experiment setup

– trajectory data obtained from the pysolo software (flies)

– larval crawling data

I want to include an automatic depository of the data in a database. Automatic entries in Figshare is for instance possible. (see older posts). My problem is to find a way to treat the data such that:

1. the raw data is uploaded

2. all data is uploaded also if we use only the centroid displacement (in some data file the head position is also given)

3. the data can be reused and data obtained in different lab, animal, setup can be compared. (data should be organized such that it can be searched and queried).

4. probably other elements that I do not think of….


My main problem: I have nearly no experience in data management/design, ontology or semantic web. Here is a first draft of a database structure that I have thought of. Every feedback would be welcome:

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automatic uplaod of data. step2

on Sunday, December 2nd, 2012 3:41 | by

Figure of result, data, raw data and code uploaded automatically. Still need to get a way to get the statistical analysis published along with it.

I will try to make a video to highlight how fast and easy it is once the code is written.

Bjoern, when do you want to present this? Do I have time or should I do it tomorrow night ? :-)

the R code was made public: everyone can access it without login

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Automatic upload of data on figshare: step1

on Wednesday, November 21st, 2012 7:38 | by


This was 100% uploaded directly from R.

First step toward automatic upload of data accomplished!

more permanent link, I think: https://dx.doi.org/10.6084/m9.figshare.97792

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LiLiu data on buridan

on Thursday, November 8th, 2012 2:50 | by

I started to work with the data I got from Li Liu. I have no metadata file, so I am not sure what will finally come out of the analysis.
What is already clear is that the number of female and male they tested seem different for each group and there is a big difference in speed between male and female… The value reported are also huge (>20 mm/s, no distinction male/female) while I get the normal 15mm/s (if the data I got is in mm and not in pixel, of course).
I do not know what GAK and ‘PAN stands for…

speedplot from liu data. X axis is not explained yet. homogenous environment, platform is 86 mm.

Remember that from our data, there is no significant difference in male versus female speed.

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Torque distribution

on Wednesday, October 24th, 2012 2:17 | by

I had seen beautiful bell shaped distribution of torque (around 0) from the Heisenberg’s lab. We thus checked the data we have (the 6 minutes data we produced with the same flies for the torque meter and compensator. Data produced on the same day, or later (when sathish was mastering the preparation a bit better).
Here is the distributions:

Our distribution are close enough to the bell shape obtain by the Heisenberg’s group. The wing beat analyser seem to lead to different torque calculation, though.
PS: no difference seen in the frequency of spikes on the other hand.

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on Tuesday, October 16th, 2012 6:02 | by

I worked on CeTrAn, corrected some bugs and added boxplot visualization of each variable. As an examples see how the stripe deviation variable vary in computer generated data, quite impressive:

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News from Neurofly

on Tuesday, September 11th, 2012 6:50 | by

A lot of things I learned at the neurofly. First my old friend Benjamin is doing a great postdoc in Bruno van Swinderen lab. It was great to see his data on isoflurane effects and the correlation between sleep disorder and sensitivity to anesthesia.

More related to our interests, I learned that Paul Tchénio has now a prototype to visualize neuronal activity in about half of the fly brain at a decent frequency. It may be interesting to get in touch with him again.

Andre Fiala is doing/has already done the TDC-Flp construct and is using his own UAS-stop-TRPA1 line to get a subset of octopaminergic neurons. Christine will contact him soon to have more information and maybe start a collaboration with him. The student was not at his/her poster when we went there, and we could not talk directly to him/her.

I nice talk by F. Mohammad (Singapore) showed that centrophobism can be associated with anxiety: the majority of treatments used with mices (for instance immobilisation in a pipet tip) also induce more (or less for some treatments) centrophobisms in flies. I told him about the CeTrAn, he said he will look at it. (his flies were in a squared box, with their wings untouched).

Jhl21 (receptor for JH) change of larval behavior at the  wandering stage (go slower and turn more): it acts at the NMJ to change the clustering of glutamate receptors. Similar thing may happen during the first hour of life of the fly, when they become phototactic ?

A nice poster from the Heisenberg’s lab show that flies do have a preferred 0 torque. Even when giving some closed loop drift, the histogram of torque suggest that the preference for the 0 torque is still there (non-uniform distribution around the +1 torque which stabilize the drift. It seems the distribution around the 0 torque is seen only if you have long enough data, I told them I would ask Satish to look at his distributions. This emphasizes why we need to be very careful in preparing the fly for our experiments…

I may have to look at the OK6 Gal4 line for motorneurons, and new RNAi lines seem to be available for PKC53e and FoxP…

I also talked to Flybase people, David was there. It seems the Buridan results should lead to 2 different entries: one linking each genotype to a dichotomic description of the phenotype (“mutant1” – “has larger”- “median_speed”) and one to the raw data and analysis. This will not be easy to automatize, but looks interesting.

I am probably forgetting a couple of things in addition to my discussion with Anette Schenk and her student Anna about FoxP..

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testing buzz data

on Thursday, October 20th, 2011 2:44 | by

looking for a platform to share our trajectory data, I got interested in buzz data. They started a little contest, and since it seemed to be a nice way to test the functionality of the web site, I participated.

I downloaded the dataset of water consumption in Canada for the last years. The data is split by year and ward. I focused on the total water consumption and ran a little analysis.

A simple ANOVA shows that the total consumption is dependent on the year, the ward and the combination of the two (this means that the differences between years consumption is not equivalent in the distinct wards). In the visualization, one can see that the mean consumption decreased in the last three years (black dots are means of consumption for each year). In the trace for each ward, we can pick particular wards with specific results. For instance ward 11 had a huge increase in consumption in 2002; and ward 2 decrease its (relative to the other very important) consumption every year since 2002.


water consumption in Toronto in the last few years in the different wards


anova results

                     Df     Sum Sq    Mean Sq  F value    Pr(>F)
data$Year             1 6.2445e+13 6.2445e+13 110.0587 < 2.2e-16 ***
data$Ward            43 5.1300e+15 1.1930e+14 210.2682 < 2.2e-16 ***
data$Year:data$Ward  43 1.0535e+14 2.4500e+12   4.3181 2.399e-15 ***
Residuals           396 2.2468e+14 5.6738e+11
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

The test show that it is quite easy to take data and perform its own analysis. Buzz data is not (yet?) very good in updating data, since there is no way to directly add data (in this case, once the 2011 data come, it will be needed to download the dataset, add the new data and reupload the new dataset. Not very convenient.

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