Events - Page 4
How can more realistic mechanical and mechanistic descriptions of organisms and their interactions make ecological models more predictive and help us understand evolution of traits, their underlying genetics and the optimality trade-offs experienced by organisms? Prof. Øyvind Fiksen (Theoretical Ecology group, Department of Biosciences) will address these and other related questions at this breakfast seminar.
What comes next once you are comfortable with the syntax of a programming language or two, and have written some small programs for yourself? Once a project grows to a certain size, factors beyond the immediate programming task take more and more time, and the social aspects of software development become more important.
Do you want to use illustrations as an effective communication tool?
The first breakfast seminar this year will be about visual data science. We are very happy to announce that Prof. Helwig Hauser, PI of the visualization group at the Department of Informatics (UiB), will talk to us about this exciting topic.
University of Bergen, Haukeland University Hospital, BTO, and Digital Life Norway invites you to a seminar focusing on dilemmas arising when you are a researcher also doing innovation, in addition to the Whys and Hows concerning patenting and publishing.
In many ways the engine of the Digital Life ambition is useful models of living systems that can explain and predict their system behaviour. Critical and constructive discussion of modelling approaches is accordingly of key importance. We will therefore also this year arrange a workshop where this is in focus.
Friday 7 Dec 2018, APT member Konstanze Kölle will have her public PhD defence at NTNU.
Welcome to this guest lecture 6 December held by Dr Chiara Toffanin (University of Pavia, Italy). She will visit NTNU, Trondheim as an opponent for Konstanze Kölle’s PhD defence, scheduled for 7 December.
The November breakfast seminar will be about mathematical modelling of animal physiology and will be given by Assoc. Prof. Susanna Röblitz, who recently started her research group at the Computational Biology Unit.
The event will gather representatives from the centre, the centre's projects, and Research School to join a search conference shaping the future of DLN towards 2020 and beyond.
Lack of new antibiotics is a major threat to the global health. The two Digital Life projects INBioPharm and Digibiotics invite to a workshop to discuss different aspects, issues and current state of antibiotic discovery, development and production.
Professor Bonnie Berger is the Simons Professor of Mathematics at MIT, holds a joint appointment in Electrical Engineering and Computer Science, and serves as head of Computation and Biology group at MIT's Computer Science and AI Lab. Her recent work focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them. She works on a diverse set of problems, including Compressive Genomics, Network Inference, Structural Bioinformatics, Genomic Privacy, and Medical Genomics. Additionally, she collaborates closely with biologists in order to design experiments to maximally leverage the power of computation for biological explorations.
ERASysAPP workshop combined with the DLN Volterra lecture.
The FAIRDOM team are arranging a satellite meeting to the International Conference on Systems Biology late October this year. More details by the FAIRDOM team below.
Centre for Digital Life Norway will offer you the opportunity to work with the innovation aspect of biotechnology and life science during a two day’s workshop, 17-18 October in Oslo.
Professor Jerome S. Engel is an internationally recognized expert on innovation, entrepreneurship, and venture capital, lecturing and advising business and government leaders around the world. Most recently he has focused on lean innovation entrepreneurship and developing innovation ecosystems globally. In the current event, he will share his insights on how this can be part of innovation in biology, health care and life science.
Throughout history many different modeling approaches has been developed to understand biological systems. What can we learn from these models?
How can organisms maintain stable internal conditions in a changing environment or during growth? The concept of homeostasis has been important for understanding physiological regulation, development of disease and more recently for bioengineering and synthetic biology.
The centre welcomes Professor Natasa Pruzlj of Biomedical Data Science at UCL to give her Volterra lecture on Friday 28 September at NTNU. She will discuss linking heterogeneous data in the biomedical domain.
We are very excited that the biannual meeting for the International Study Group for Systems Biology (ISGSB) will be in Norway, Tromsø, this year! Centre for Digital Life Norway is involved in the event, which brings together systems biologists and mathematical modellers from around the world.
The course builds on approaches and technologies that we are currently developing in the NTNU DrugLogics initiative, where we use the logical modelling formalism for predicting the outcome of chemical perturbations (cancer drugs) on cancer cell fate decisions. This approach combines knowledge management, logical model construction and computational simulation with experimental assays and hypothesis testing for pre-clinical (biotechnological) drug development and clinical decision support. The course will exemplify how such approaches can be used in both the biotechnological and biomedical sectors such as pre-clinical drug discovery and repurposing, and clinical development of diagnosis and (combinatorial) treatment of cancer.
The annual conference of Digital Life Norway Research School is organized for and by the research school members.
This year's innovation day is part of the Life science Technology & Business Conference - " 37° - Digitalising Health", 19 - 20 June 2018, Stavanger, Norway.
Welcome to an academia-industry meeting day, AIMday®, focused on the use of machine learning in life science and medicine. Machine learning, in which systems automatically learn complex patterns in data, and improve from experience, is becoming an essential tool in healthcare diagnosis, treatment and care, as well as in medical research.