COMPUTATIONAL ECOTOXICOLOGY

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Image: Logo Institute for Environmental Research

RESEARCH: Profile, Projects, Publications
TEACHING: Courses, Supervision
DATA LAB: Seminars, Presentations, R-Howto, Meet us
NETWORK: Team, Partners, Funding
ABOUT: Contact, Impressum

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RESEARCH: Profile

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The working group Computational Ecotoxicology at the Institute for Environmental Research focuses on complexity in structures and processes of hierarchical dynamical bio-systems. Our research concentrates on three main objectives: (1) Solving ecological questions and problems with computational methods, (2) Understanding the nature of ecological systems as computing entities and (3) Developing computational methods by learning from other disciplines in an interdisciplinary way.

Png: Pieces of the Computational puzzle

We develop hybrid mathematical and machine learning algorithms and methods for multivariate modelling, pattern recognition, causal analysis and prediction in life-science disciplines like ecology, ecotoxicology and risk assessment. To link different lines of evidence (i.e. theory, simulation and observation) techniques from statistical pattern recognition, machine learning, data mining and bioinformatics as well as approaches from complex systems theory and chaos theory are used in a wide field of applications. More detailed attention is paid to non-linear dynamics, self-organization processes, the role of information and entropy, the integration of expert knowledge into modelling processes as well as epistemological consequences.

In our most recent research we apply the developed methods in questions about Chemo-behavioral profiling using Danio rerio video tracking data and Expert-augmented statistics in ecotoxicological bio-testing. Special long-term research topics we are interested in are Non-linear dynamics (Bifurcation and chaotic dynamics and their implications for the stability and resilience of natural agent-based systems), Entropy (Negentropic information flow and its relation to self-organization in dissipative living systems), Networks (Integration of theory and observations to assess ecosystem integrity), Complexity (Emerging phenomena and their relevance to ecological structures and dynamics) and Limitations (Gödel’s incompleteness theorems and their implications for modelling in the life sciences).

Understanding of patterns and processes in living systems requires a flexible range of data analysis techniques. Simulation using mathematical models, statistics and theoretical analysis of model equations are important generic tools to interpret and underpin results from lab and field observations. These in-silico-experiments are equally relevant to setting up and analysing laboratory experiments. They allow integration of empirical observations and theoretical models to generate and test multifactorial hypotheses. Such a system-oriented approach helps to elucidate structures, processes and dynamics in complexly interacting biological systems, e.g. ecological communities, gene expression networks and the immune system.

For further details see the projects section. Here you can download a short COPE working group profile.

Animated Gif: A neural network showing different activation patterns from a carabid assemblage data set Png: A species community network in a tropical forest regeneration site, showing trophic interaction structure Animated Gif: An error optimization algorithm gets trapped in a local minimum Png: A wordle, displaying important research topics (all figures copyright R. Ottermanns) Animated Gif: PCA analysis of phytoplankton communities in a mesocosm experiment, showing temporal trajectories of community composition (red: control, blue: treatment)
From left to right: A neural network showing different activation patterns from a carabid assemblage data set, a species community network in a tropical forest regeneration site with hierachical trophic structure, an error optimization algorithm gets trapped in a local minimum, a wordle displaying important working group topics, a PCA analysis of phytoplankton communities in a mesocosm experiment (showing temporal trajectories of community composition, red: control, blue: treatment) (All Figs. (c) R. Ottermanns)


RESEARCH: Projects

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RESEARCH: Publications

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Peer reviewed journals:

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TEACHING: Courses and lectures

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For details about courses please go to RWTH Online. All courses are taught in German, English on request.

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TEACHING: Supervision

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Current:

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DATA LAB: Seminars

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Methodological Seminar in Data Science and Machine Learning

The methodological seminar is meant to inform about actual methods everyone can use in her/his scientific work. It is a professional training for the working group members but also for all interested people from the institute. Topics are developed at the moment. Exact dates will be published when a topic is ready to run. If you want to join one of the topics please register by sending an e-mail to ottermanns@ifer.rwth-aachen.de.

In preparation:


DATA LAB: Presentations

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Official presentations are given in the institute seminar or the working group colloqium. TechTalks are a more informal way to present project ideas, discus methods, related problems or astounding findings with your collegues. Feel free to choose your favorite way of presentation. Use slides, meditative speed dating or a dada performance. According to Paul Feyerabend: Anything goes.


DATA LAB: R-Howto

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Here you can find our latest R-Howto:


DATA LAB: Meet us

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NETWORK: Team

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Ottermanns, Richard, Dr. rer. nat. Dipl.-Ing. Dipl.-Biol.

Photo: Richard Ottermanns

Actual bibliometrics from Web of Science/Google Scholar (15.11.2024):

Room: 231
Tel: +49-241-8026688
Mail: ottermanns(at)ifer(dot)rwth-aachen(dot)de
Web: https://cope.rwth-aachen.de
Office hours: On appointment
Business card: download

Byun, Jaegyun, MSc

Photo: Jaegyun Byun

Mail: jaegyun(dot)byun(at)bio5(dot)rwth-aachen(dot)de

Ludwig, Franziska, BSc

Photo: Franziska Ludwig

Mail: franziska(dot)ludwig1(at)rwth-aachen(dot)de

Schröder, Katja, MSc

Photo: Katja Schröder

Room: 253
Tel: +49-241-8027626
Mail: katja(dot)schroeder(at)bio5(dot)rwth-aachen(dot)de

Torringen, Volker

Photo: Volker Torringen

Room: 251
Tel: +49-241-8023693
Mail: v(dot)torringen(at)bio5(dot)rwth-aachen(dot)de


NETWORK: Partners

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Recent projects:

Former projects:


NETWORK: Funding

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ABOUT: Contact

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Dr. rer. nat. Dipl.-Ing. Richard Ottermanns
Computational Ecotoxicology (COPE)
Institute for Environmental Research (IFER)
Department of Ecology & Computational Life Science
RWTH Aachen University
Worringerweg 1
D-52074 Aachen
Germany

Room: 231
Tel: +49-241-8026688
Mail: ottermanns(at)ifer(dot)rwth-aachen(dot)de
Web: https://cope.rwth-aachen.de
Business card: download


ABOUT: Impressum

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Umsatzsteuer-Identifikationsnummer

Gemäß § 27 a Umsatzsteuergesetz: DE 121689807

Inhaltliche Verantwortlichkeit

Ansprechpartner: Dr. Richard Ottermanns

Telefon: +49 241 80 26688

E-Mail: ottermanns(at)ifer(dot)rwth-aachen(dot)de

Webmaster: Dr. Richard Ottermanns

Telefon: +49 241 80 26688

E-Mail: ottermanns(at)ifer(dot)rwth-aachen(dot)de

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