Three Algorithms Inspired by Data from the Life Sciences

Event type: 
Guest lecture
Event time: 
22.05.2017 - 10:15 - 11:00
Lecturer : 
Allan Tucker
Place: 
Exactum D123, Kumpula
Description: 

Dr Allan Tucker (Brunel University, UK) will visit us on Monday, 22nd May, and present the following talk. Dr Tucker will also be available for discussions on the day of the talk.

A simulated time series from a three-state HMM for modelling disease progression. Source: Allan Tucker.

Three Algorithms Inspired by Data from the Life Sciences

Abstract:  In this talk I will discuss how the analysis of real-world data from health and the environment can shape novel algorithms. Firstly, I will discuss some of our work on modelling clinical data using probabilistic graphical models (dynamic Bayesian networks, and hidden Markov models). In particular I will discuss the collection of longitudinal data and how this creates challenges for diagnosis and the modelling of disease progression that can be overcome with latent variables. I will then discuss how cross-sectional studies offer additional useful information that can be used to model disease diversity within a population but lack valuable temporal information. Finally, I will discuss the importance of inferring models that generalise well to new independent data and how this can sometimes lead to new challenges, where the same variables can represent subtly different phenomena. Some examples in ecology and genomics will be described.

 

Short bio: Dr Tucker's first degree was in Cognitive Science at Sheffield University, UK, where he became interested in models of brain function and human and animal behaviour. His other interests include learning models of time-series data in order to try and understand the underlying processes, with a focus on biological, clinical and ecological data. He received his Ph.D at Birkbeck College, University of London sponsored by the Engineering and Physical Sciences Research Council; Honeywell Hi-Spec Solutions, UK; and Honeywell HTC, USA. As a Senior Lecturer at Brunel University London he leads the Intelligent Data Analytics Research group. He has worked in conjunction with Leiden University Medical School and University College London on gene regulatory networks. His current projects include modelling high dimensional gene expression data with Rothamsted Research; modelling visual field test data from Moorfield's Eye Hospital, London; text mining flora with the Royal Botanical Gardens,  Kew London; an epidemiological big data analytics project in Kazakhstan funded by the British Council; and exploring the dynamics of fish populations in the Northern Atlantic in conjunction with the Canadian Department of Fisheries and Oceans and DEFRA.
 
 
Welcome!
 
Host: Teemu Roos, teemu.roos@cs.helsinki.fi.

 

15.05.2017 - 13:42 Teemu Roos
13.05.2017 - 12:58 Teemu Roos