B-IT professors organise a lecture series in Summer Semester 2015. This summer semester it is organised by:

• Professor Dr. Jürgen Bajorath (Life Science Informatics)
• Professor Dr. Christian Bauckhage (Media Informatics)
• Professor Dr. Hofmann-Apitius (Life Science Informatics)
• Dr. Holger Fröhlich, Dept. of Computer Science, University of Bonn (Life Science Informatics)

Venue : B-IT Lecture hall
Time : 17.00 hours 

21 May 2015

Dr. Mark Coles York University, Centre for Immunology and Infection, United Kingdom 

Abstract 

In the York Computational Immunology Laboratory we have been combining experimental immunology with computational and mathematical approaches to understand mechanisms driving immunity to pathogens, inflammatory disorders and autoimmune disease. Immune responses occur in specialised microenvironments where stochastic interactions between different immune cells and secreted factors (cytokines/chemokines), leads to the emergence of immunity.

In this talk I will describe the modelling process (based on the COSMOS process) of generating transparent models using a suite of tools we have developed including the ARTOO argumentation tool, SPARTAN (statistical analysis tool) and VBIS (Visualisation and Quantification of Biological Simulations) to document and parameterise the simulations, and communicate with experimental scientists. As an experimental immunologist my research focuses on how immune microenvironments are established, how they can be remodelled and how this can lead to efficient immune responses using a number of different approaches including imaging, genomics, functional assays, mathematical and computation modelling. In this seminar I will discuss how through using a cyclical approach of hypothesis driven modelling and experimentation we have developed new insights into the molecular and cellular mechanisms driving immune function. I will focus on three different examples, where we have used different modelling approaches; agent based models, multi-scale simulations and mathematical models to address questions that could not be answered by experimentation alone and describe the rational for the different modelling approaches. Finally I will discuss how we are applying critical systems engineering approaches to human disease modelling to accelerate and de-risk the drug development pathway and integrate bioinformatics data into computational simulations. 

Suggested Literature by the Lecturer

1. Using argument notation to engineer biological simulations with increased confidence. K.Alden, P.S.Andrews, F.A.C.Polack, H.Veiga-Fernandes, M.C.Coles, J.Timmis. Journal of the Royal Society Interface. doi: 10.1098/rsif.2014.1059 
2. Determining Disease Intervention Strategies Using Spatially Resolved Simulations. M. Read, P. Andrews, J. Timmis, R. Williams, R. Greaves, H. Sheng, M. Coles and V. Kumar. PLoS ONE 8(11): e80506. doi:10.1371/journal.pone.0080506 
3. SPARTAN: A Comprehensive Tool for Understanding Uncertainty in Simulations of Biological Systems. K. Alden, M. Read, J. Timmis, P.S. Andrews, H. Veiga-Fernandes, M.C. Coles. PLoS Comput Biol 9(2): e1002916. doi:10.1371/journal.pcbi.1002916 
4. Differential RET signaling responses orchestrate lymphoid and nervous enteric system development. A. Patel, N. Harker, L. Moreira-Santos, M. Ferreira, K. Alden, J. Timmis, K. Foster, A. Garefalaki, P. Pachnis, P.S. Andrews, H. Enomoto, J. Milbrandt, V. Pachnis, M.C. Coles, D. Kioussis, H. Veiga-Fernandes. Science Signalling, Volume 5, Issue 235. doi: 10.1126/scisignal.2002734 
5. Pairing experimentation and computational modelling to understand the role of tissue inducer cells in the development of lymphoid organs. K. Alden, J. Timmis, P.S. Andrews, H. Veiga-Fernandes, M.C Coles. Frontiers in Immunology. Volume 3:172. doi: doi: 10.3389/fimmu.2012.00172.

Read more about the lecturer and his work...

11 June 2015 

Professor Dr. Kristian Kersting Technical University of Dortmund, Germany 

Abstract

Understanding the response dynamics of plants to biotic stress is essential to improve management practices and breeding strategies of crops and thus to proceed towards a more sustainable agriculture in the coming decades. In this context, hyperspectral imaging offers a particularly promising approach since it provides non-destructive measurements of plants correlated with internal structure and biochemical compounds. In this talk, I shall discuss a cascade of data mining techniques for fast and reliable data-driven sketching of complex hyperspectral dynamics in plant science and plant phenotyping. More precisely, I shall touch upon a recent linear time matrix factorization technique, called Simplex Volume Maximization, and show how to use it in order to automatically discover archetypal hyperspectral signatures that are characteristic for particular diseases: barley leaves (Hordeum vulgare) diseased with foliar plant pathogens Pyrenophora teres, Puccinia hordei and Blumeria graminis hordei. Towards more intuitive visualizations of plant disease dynamics, I shall then show how to use the archetypal signatures to create structured summaries that are inspired by metro maps, i.e. schematic diagrams of public transport networks. Metro maps of plant disease dynamics produced on several real-world data sets conform to plant physiological knowledge and explicitly illustrate the interaction between diseases and plants. Most importantly, they provide an abstract and interpretable view on plant disease progression. 

This talk is based on 

• Wahabzada, Mirwaes and Mahlein, Anne-Katrin and Bauckhage, Christian and Steiner, Ulrike and Oerke, Erich-Christian and Kersting, Kristian. Metro Maps of Plant Disease Dynamics - Automated Mining of Differences Using Hyperspectral Images. In PLoS ONE, 2015. 

and the following previous work: 

• C. Roemer and M. Wahabzada and A. Ballvora and F. Pinto and M. Rossini and C. Panigada and J. Behmann and J. Leon and C. Thurau and C. Bauckhage and K. Kersting and U. Rascher and L. Pluemer. Early Drought Stress Detection in Cereals: Simplex Volume Maximization for Hyperspectral Image Analysis. In Functional Plant Biology, Vol. 39, Seiten 878-890, CSIRO Pblishing, 2012. 
• M. Wahabzada and K. Kersting and C. Bauckhage and C. Roemer and A. Ballvora and F. Pinto and U. Rascher and J.Leon and L. Pluemer. Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants. In de N. Freitas and K. Murphy (editors), Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, California, USA, 2012. 
• K.Kersting and Z. Xu and M. Wahabzada and C. Bauckhage and C. Thurau and C. Roemer and A. Ballvora and U. Rascher and J. Leon and L. Pluemer. Pre-symptomatic Prediction of Plant Drought Stress using Dirichlet-Aggregation Regression on Hyperspectral Images. In Twenty-Sixth Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012. 
• Thurau, Christian and Kersting, Kristian and Wahabzada, Mirwaes and Bauckhage, Christian. Descriptive Matrix Factorization for Sustainability -- Adopting the Principle of Opposites. In Data Mining and Knowledge Discovery, Vol. 24, No. 2, Seiten 325-354, Springer, 2011.

Read more about the lecturer and his work... 

15 June 2015 

(Please note: 15 June 2015 is no Thursday, but a Monday!) 

Dr. Veerabahu Shanmugasundaram Director & Head of Computational Analysis and Design Center of Chemistry Innovation & Excellence World Wide Medicinal Chemistry Pfizer Pharma Therapeutics Research & Development 

16 June 2015 

Dr. Veerabahu Shanmugasundaram Director & Head of Computational Analysis and Design Center of Chemistry Innovation & Excellence World Wide Medicinal Chemistry Pfizer Pharma Therapeutics Research & Development 

Gartensaal, 11.00 hours

Lecture with discussion

This talk is part of B-IT career service.

18 June 2015 

Michaela Torkar Editorial Director at Faculty 1000 Research (F1000Research), London, United Kingdom. 

Important notice: This talk will be deliverend in B-IT Rheinsaal as an exception. 

Abstract

The Faculty of 1000 (F1000) is a provider of innovative and unique services that support the work of life scientists and clinicians around the globe. This presentation will highlight two of these services aimed at assisting in writing, discovering and sharing science. F1000Research, published by Faculty of 1000, is a relatively new Open Science publishing platform that aims to address limitations of the traditional publishing process, such as publication bias towards ‘positive’ and 'interesting' results; protracted peer-review processes; and lack of source data in publications that reduce the reproducibility of the presented results. 

To address these issues, F1000Research publishes research across all life sciences, irrespective of the perceived level of interest and novelty. It operates a post publication peer review model, offering rapid publication without editorial bias and fully transparent peer review by invited experts. F1000Research also insists on the inclusion of source data in easily accessible formats and on detailed descriptions of methods, making it easier for others to repeat the analysis presented in an article. 

To further support scientists, F1000 has just launched a new authoring tool that will revolutionise the way that researchers write and collaborate. The tool covers all aspects of writing a research article; from literature discovery and reference management to sharing and annotating papers with collaborators in a safe and secure environment. The F1000 Workspace software incorporates over 150,000 article recommendations written by more than 5,000 eminent scientists and clinical researchers who have been systematically surveying the scientific literature over the past decade for the most relevant publications in their fields. 
By creating tools for scientists to write, discover and share science, F1000 aims to make science and publishing fast, easy, transparent and reproducible.

Biography

Michaela Torkar has a degree in biology from the Ludwig-Maximilians-Universität in Munich and a PhD in Immunology from the University of Cambridge, UK. She joined the first Open Access publisher, BioMed Central, when it launched in 2000 as a member of the editorial team of Genome Biology, the Editor of which she was for two years (2006-2008). She was Editorial Director at BioMed Central for several years before she joined F1000Research in 2014. 

Read more about F1000

2 July 2015 

Professor Dr. Viktor Jirsa Director of the Institute de Neurosciences des Systèmes, Université Aix-Marseille and Director of Research at the CNRS, France

Abstract

Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they can be induced in a normal brain under a variety of conditions in most neuronal networks and species from flies to humans. Such universality raises the possibility that invariant properties exist that characterize seizures under different physiological and pathological conditions. Starting from first principles of the theory of slow-fast systems in nonlinear dynamics, we conceptualize seizure dynamics mathematically and establish a taxonomy of seizures based on seizure onset and offset bifurcations. We demonstrate that only five state variables linked by integral-differential equations are sufficient to describe the onset, time course and offset of ictal-like discharges as well as their recurrence. These state variables define the model system called the Epileptor, where two state variables are responsible for generating rapid discharges (fast time scale), two for spike and wave events (intermediate time scale) and one permittivity variable (slow time scale). The permittivity variable captures effects evolving on slow timescales, including extracellular ionic concentrations and energy metabolism, with time delays of up to seconds as observed clinically. We propose that normal and ictal activities coexist: a separatrix acts as a barrier (or seizure threshold) between these states. Seizure onset is reached upon the collision of normal brain trajectories with the separatrix. We show theoretically and experimentally how a system can be pushed toward seizure under a wide variety of conditions. Within our experimental model, the onset and offset of ictal-like discharges are well-defined mathematical events: a saddle-node and homoclinic bifurcation, respectively. These bifurcations necessitate a baseline shift at onset and a logarithmic scaling of interspike intervals at offset. These predictions were not only confirmed in our in vitro experiments, but also for focal seizures recorded in different syndromes, brain regions and species (humans and zebrafish). Extending this generic approach rooted in nonlinear dynamics towards human brain networks, we reconstruct personalized connectivity matrices of human epileptic patients using Diffusion Tensor weighted Imaging (DTI). Subsets of brain regions generating seizures in patients with refractory partial epilepsy are referred to as the epileptogenic zone (EZ). During a seizure, paroxysmal activity is not restricted to the EZ, but may recruit other brain regions and propagate activity through large brain networks, which comprise brain regions that are not necessarily epileptogenic. The identification of the EZ is crucial for candidates for neurosurgery and requires unambiguous criteria that evaluate the degree of epileptogenicity of brain regions. Stability analyses of propagating waves provide a set of indices quantifying the degree of epileptogenicity and predict conditions, under which seizures propagate to nonepileptogenic brain regions, explaining the responses to intracerebral electric stimulation in epileptogenic and nonepileptogenic areas. We demonstrate the predictive value of our seizure propagation model by validating it against empirical patient data. In conjunction, our results provide guidance in the presurgical evaluation of epileptogenicity based on electrographic signatures in intracerebral electroencephalograms. 

Biography and selected papers

 9 July 2015 

PD Dr. Nikolaos Koutsouleris Klinik für Psychiatrie der Ludwig Maximilians Universität München, Germany 
 
More information about Dr. Koutsouleris and his work

12 August 2015  

Daniel Damian, PhD Centre Leenaards de la Memoire – CHUV University Hospital of Lausanne, Switzerland

Abstract 

Dr. Damian will present practical experiences on deploying text analytics techniques with the aim of extracting medical data from natural language text within patient records at the memory clinic of the University Hospital of Lausanne. He discusses steps taken for the creation of a domain-oriented medical terminology and its use in the recognition of medical concepts, as well as work for extracting numerical attributes corresponding to clinical assessment scores. He also discusses how combining these techniques with adoption of standards in the day-to-day practice can improve the quality and efficiency of data collection within the clinic.