next talk: A Bayesian t test using PyMC, 1 February 2013

[Andrew Straw]

A Bayesian t test using PyMC

Andrew Straw, IMP

Friday, 1 February 2013, 12:30pm, GMI Orange Seminar Room (room 9.36)

Across many branches of biology, null hypothesis significance testing is the tried-and-true method of establishing whether an effect is “real”. Nevertheless, many pitfalls must be avoided to correctly evaluate statistical significance and it is easy to make mistakes that render the analysis invalid. I will summarize a recent paper Bayesian estimation supersedes the t test (“BEST”) by John Kruschke (2012, Journal of Experimental Psychology: General.). Kruschke’s Bayesian approach purports to acheive the same goals as the t test with fewer potential pitfalls. Furthermore, his approach has several advantages, such as the ability to accept the null hypothesis. Computationally, credible intervals of important parameters such population means and effect size are found using Monte-Carlo techniques such as the Metropolis-Hastings algorithm. I will discuss a Python implementation of the BEST algorithm written using PyMC.

[Wolfgang Busch]

Dear all,

this is the Web-app that I mentioned in the discussion today.

http://www.sumsar.net/best_online/

Cheers, Wolfgang

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[Huber Ludwig]

Dear Andrew,

may I ask you a favor? Do you know an open source solution for motion tracking that could be used to track the wagging of a dog's tail? Ideally without markers, but if necessary we could also imagine to fix reflective or highly visible paper markers on the tail.

If you don't immediately have an answer, do you you know whom we may ask as well?

Thank you for your help,

best wishes,

Ludwig

Prof. Ludwig Huber, PhD

Head of Comparative Cognition 
Messerli Reserach Institute

University of Veterinary Medicine, Vienna (Vetmeduni Vienna)
Veterinaerplatz 1, 1210 Vienna, Austria

T +43 1 25077-2680
M +43 664 60257-6250
ludwig...@vetmeduni.ac.at
www.vetmeduni.ac.at/messerli

Partner institutions of the Messerli Research Insitute:

Messerli-Foundation, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna

[Straw,Andrew]

CellCognition: A tool for time-resolved phenotype annotation in high-throughput live cell imaging

Christoph Sommer, IMBA

Friday, 5 April 2013, 12:30pm, GMI Orange Seminar Room (room 9.36)

Automated microscopy has become an enabling technology to monitor and quantify properties of cells. A typical workflow to analyze microscopy data comprises the segmentation of cells, linking of cell objects over time, and quantification of cellular phenotypes. CellCognition is published as open source software, enabling automated analysis of live-cell image-based screening data.

[Straw,Andrew]

CellCognition: A tool for time-resolved phenotype annotation in high-throughput live cell imaging

Christoph Sommer, IMBA

Today, Friday, 5 April 2013, 12:30pm, GMI Orange Seminar Room (room 9.36)