We want to bring together young researchers in Sweden working on the border of math, biology, and medicine.

The Workshop

We are pleased to invite you to our Workshop on Modelling in Biology and Medicine (MBM). The workshop will take place on 9th and 10th May 2019 in Gothenburg, Sweden. We aim to gather all young researchers in Sweden working on modelling of biological systems. Our ambition is to give all participating PhD students and PostDocs the opportunity to present their work through an oral presentation or a poster. Further, we wish to provide an insight on how modelling in biology and medicine is practiced in academia and industry.

We are looking forward to meeting you at the MBM workshop!

A selection of topics that are suitable for posters and talks at this workshop. Topics not on this list but related to modelling in biology or medicine are also very welcome!

Kinetic modelling Rule-based modelling Boolean modelling Spatial modelling Machine learning / Deep learning Network modelling Statistical modelling Stochastic modelling Gene regulation Multi-scale modelling Biomarkers Cancer Systems biology Synthetic biology Pharmacokinetics Pharmacodynamics Drug target discovery Genome-scale metabolic models Bioinformatics Evolutionary biology Theoretical biology

Who we are

We are a small group of doctoral students working at the Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, as well as the Department of Systems and Synthetic Biology, Chalmers University of Technology.

Organizing committee

Invited Speakers

Matteo Barberis

Reader/Professor in Systems Biology at the University of Surrey in Guildford, UK

Matteo has recently become professor at the University of Surrey and has a background in industrial biochemistry, molecular biology and computational modelling. His research focuses on integrating experimentation and computation to gain insight on cellular organization. His main areas of focus are temporal control of gene regulation of cell cycle control and multi-scale frameworks that integrate cellular regulation.

Matteo Barberis

Photo via Personal Website

Title Systems biology to decipher design principles of cellular networks
Abstract Continuity of life is sustained by time-dependent responses of biological networks that are associated to oscillatory behavior of their components, at a proper frequency. The eukaryotic cell cycle is such an example, with waves of enzymatic activities being tightly regulated to guarantee its frequency. Therefore, molecular designs that exhibit a proper frequency of enzymatic oscillations are inherently crucial for a timely cell cycle progression. In this talk, I will show how computational frameworks, such as kinetic modelling, Boolean modelling, and multi-scale modelling, may serve the purpose of investigating how a timely cell cycle progression is achieved, possibly resulting in the identification of novel principle of design that ensures a timely cell cycling.

Francesco Gatto

Guest Researcher at Chalmers and Co-Founder + Chief Scientific Officer at Elypta

Named Winner of MIT Technology Review's Innovators Under 35 in 2018, Francesco co-founded Elypta in 2017, a molecular diagnostics start-up focussed to improve the survival outlook of cancer patients by developing systems biology-driven biomarkers. He invented a diagnostic and prognostic test for renal cell carcinoma based on an exceptionally accurate liquid biopsy, which leveraged on a novel systems biomarker for this common form of kidney cancer. This test recently showed unprecedented potential for other cancer types.

Title From systems biology research to a diagnostic start-up
Abstract An ultimate goal of fundamental research is to improve the life of our people. Systems biology research can help patients to live better and longer by integrating data on their disease into personalized treatment. This is the core of precision medicine and requires innovation in therapeutics and diagnostics. During this talk, I will show an empirical model to make precision medicine a reality, a path set forth by innovation and a path that scientists have a privileged if not an exclusive access to. I will illustrate this model within the context of my own journey with Elypta, a molecular diagnostics start-up I cofounded in 2017 starting from a systems biology research project initiated during my doctoral studies.

Peter Gennemark

Principal scientist at AstraZeneca R&D and Adjunct Assoc Prof in Systems Biology at Linköping University

Peter works on mathematical modelling of biological systems and their interactions with drugs (systems biology and pharmacokinetics/pharmacodynamics). He is focusing on systems relevant for metabolic and cardiovascular diseases. In his work, he develops and analyses mathematical models of different granularity, and apply them in the preclinical phase of drug discovery. He collaborates closely on systems biology research topics with Gunnar Cedersund at Linköping University, for instance on modelling of micro-physiological (organ-on-a-chip) systems.

Title Mathematical modelling in preclinical drug discovery
Abstract The talk generally describes what type of mathematical models are used in the preclinical phases of drug discovery in the pharmaceutical industry, and how these models are implemented and applied in the discovery process. Focus is on how to translate the pharmacokinetics and the pharmacodynamics of a drug candidate between in vitro systems, animal models and humans. The talk includes several specific examples from the metabolic and cardiovascular areas.

Adil Mardinoglu

Professor of Systems Biology at King’s College London, UK and Royal Institute of Technology (KTH), Sweden

Dr. Adil Mardinoglu works as a Professor of Systems Biology at King’s College London, UK and Royal Institute of Technology (KTH), Sweden. His main area of expertise is in Systems Biology/Medicine, Computational Systems Biology and Bioinformatics (http://sysmedicine.com). His research focuses on the generation of the context specific biological networks for human cells/tissues as well as certain types of cancer including hepatocellular carcinoma by integrating multi-omics data. Such comprehensive networks are employed to identify novel biomarkers and drug targets that can be used for the development of effective treatment strategies for NASH/NAFLD and other obesity-associated disorders. Dr. Mardinoglu is co-founder of two companies focusing on the development of therapies for liver associated diseases.

Adil Mardinoglu

Photo via 86th EAS congress

Title The use of systems biology in treatment of liver diseases
Abstract To develop novel strategies for prevention and treatment as well as to gain detailed insights about the underlying molecular mechanisms of liver diseases, it is vital to study the biological functions of liver and its interactions with other tissues and gut microbiota. Biological networks can provide a scaffold for studying biological pathways operating in the liver in connection with disease development in a systematic manner. In my presentation, I will present our recent work where biological networks have been employed to identify the reprogramming in liver physiology in response to NASH/NAFLD. I will further discuss how this mechanistic modelling approach can contribute to the discovery of biomarkers and identification of drug targets which may lead to design of targeted and effective treatment strategies.
Keypoints
  • Omics technologies are used in detailed characterization of human liver tissue in health and disease states.
  • Biological network models are functional tools for exploring and integration of multiomics data.
  • Systems biology uses a holistic and integrative approach for comprehensive analysis of the biological functions in healthy and diseased states.
  • Systems Biology approaches have been successfully employed in hepatology to identify biomarkers and drug targets.
  • These integrative tools can be used for simulation of liver tissue functions and its crosstalk with other tissues for prediction of therapeutic and side effects.

Marina Rafajlović

Assistant Professor at Gothenburg University, Marine Sciences

Marina has recently become Assistant Professor at the Department of Marine Sciences, University of Gothenburg, and she is a member of the Centre for Marine Evolutionary Biology, University of Gothenburg. Marina has a background in Physics and Theoretical Biology. Her main research interests are within Evolutionary Biology. Specifically, she is interested in the mechanisms of speciation, species' range expansions and the evolutionary advantages of sexual reproduction. Marina's research method involves mathematical modelling (individual-based computer simulations) with model results serving as an input against which empirical genetic data are tested. Marina has recently been awarded a grant by the Hasselblad Foundation for developing her research on the evolution of populations undergoing range shifts, specifically focusing on short- and long-term potential for local genetic adaptation in expanding populations.

Marina Rafajlovi

Photo via ResearchGate

Title Unfolding evolution using mathematical models
Abstract Evolution, the change in the heritable characteristics of biological organisms over successive generations, is the fundamental process responsible for producing and maintaining biodiversity. Over time, an evolving species may face either extinction (e.g. due to the poor potential of its individuals to cope with environmental conditions they encounter), or speciation – the species' split into two (or more) reproductively isolated species (e.g. when individual populations of the species encounter contrasting environmental conditions). Distinguishing the evolutionary mechanims leading to the former or the latter outcome is challenging to date. However, because heriatable characteristics have a genetic basis, patterns of genetic variation within a population are necessarily shaped by the evolutionary history of the population. Therefore, much of the evolutionary mechanism at work in a given population can be learned from empirical patterns of genetic variation in the population. Importantly, to interpret genetic data, it is necessary to produce theoretical expectations for how different evolutionary mechanims and their interplay shape genetic variation during evolution. In this talk, I will highlight some of the recent theoretical advances in the field, specifically focusing on new theoretical insights and open questions in speciation research.

PhD student and PostDoc Speakers

To be anounced

Program

9th May

Time Activity
13.00 Registration
14.00 Talk: Matteo Barberis
14.30 Talk: Adil Mardinoglu
15.00 Coffee and posters ("Group A")
16.00 Oral presentations by PhD-students and PostDocs
18.30 Dinner

10th May

Time Activity
8.30 Invited Speaker
9.00 Talk: Francesco Gatto
9.30 Coffee and posters ("Group B")
10.30 Oral presentations by PhD-students and PostDocs
12.00 Lunch
13.00 Oral presentations by PhD-students and PostDocs
14.00 Talk: Peter Gennemark
14.30 Talk: Marina Rafajlović
15.00 Coffee and posters ("Group C")
16.00 Invited speakers
17.00 Departure

Location

The workshop will be held at the Wallenberg Conference Center, room Europe.

Registration

Important information:

Registration deadline
Prolonged: Until 5th April 2019 25th April 2019.
Participants/presenters will be continuously contacted as soon as possible after registration.
Registration fee
  • No registration fee for PhD students and PostDocs
  • 800 SEK for senior academic and non-academic participants.
Additional information
  • Talks are going to be 15 min + additional 5 min for questions
  • PhD students will be able to receive 1.5 credits from the University of Gothenburg when presenting a poster or holding a talk.
  • Depending on the number of registered participants, we want to reserve the right to limit dinner participation to presenters, observing PhD students and PostDocs as well as fee-paying participants. However, feel free to sign up for the dinner even if you are not part of this group. We will let you know if there is enough space.
I want to participate at the dinner
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