Credits: 7.5 ECTS
3-6 October, Selbusjøen hotel
1-2 December, NTNU
Project work in-between plenary meetings
Registration is closed.
This course is for all PhD students and post-doctors who want to learn more about working on transdisciplinary research projects within biotechnology and the life sciences. The main part of the course will be to work directly on a pre-defined research project with real datasets (see below for choices) with a highly skilled supervisor and an interdisciplinary team. In the plenary sessions, there will be special focus and training on how to work in interdisciplinary research groups, common interdisciplinary challenges and possible solutions, data management, and how to implement the principles of RRI (responsible research and innovation) in your research. Participants with a background in life sciences, biotechnology, bioinformatics, mathematics, or computer science are encouraged to apply.
Structure of the course
The course is composed of 3 teaching blocks:
- A start-up plenary (3-4 days) at Selbusjøen hotel, where participants will be introduced to the different scientific projects that constitute the scientific part of the course. The start-up plenary will also cover the essentials of interdisciplinary group work, introduction to remote collaboration and sharing of big data, and introduction to RRI.
- The group projects offered in the course are based on scientific data made available by the group leader and their research group. The students will learn about the data collection and their importance in generating new knowledge and/or innovation. Each group work will consist of one or more tasks linked to modelling and/or analysis of the data.
- The final plenary session (2 days) will take place at NTNU and will contain presentations of the work and results from all scientific projects. There will also be round-table discussion and sharing of experiences on transdisciplinary group work and collaboration.
The start-up plenary will cover:
- Practical information about the course including information about the evaluation method
- Discussions on responsible research and innovation, with (DLN/UiB/NTNU).
- Practical lessons and experiences on working in interdisciplinary research groups.
- Scientific introduction to the projects led by the project leaders (in groups)
Harnessing data from biodiversity genomics projects
Biodiversity genomics projects such as Darwin Tree of Life, European Reference Genome Atlas and our own Earth BioGenome – Norway (EBP-Nor) are generating high quality reference genome assemblies for a multitude of species. The goals of these projects are to create a better understanding of biology and evolution, conserve biodiversity and to create benefits for society and human welfare – including biotechnological use. In this project we will look at how we can utilize data that are generated by the biodiversity projects to better understand the biology of different species, and how this can inform medicine or biotech. Comparative genomics is a key concept here, and extracting information from whole-genome multiple alignments and/or a catalogue of orthologous gene relationships are examples of key approaches that can be used.
Fluctuations in fluorescence imaging for nanoscopy of living and fixed cells
Can we see features as small as 50-100 nm using a wide-field fluorescence microscope capable of resolving features as big as 250 nm? Can we image living cells with this super-resolution? This project is about simple technical solutions, namely fluorescence fluctuation based nanoscopy techniques, for these two problems. Natural photokinetic properties of fluorescent molecules result into unique signatures, which can be used for super-resolution without introducing harmful chemicals or intense laser light onto living cells. We will explore four such nanoscopy techniques namely MUSICAL, SRRF, SACD, and ESI using pre-acquired image datasets.
Network inference using single cell gene expression data
In this project, we will tackle the challenge of learning regulatory networks from individual cells in our body using single cell transcriptomic data. Multicellular organisms including humans have same DNA in every cell, nevertheless the cells of every organ need to perform a highly specific function. The key question therefore is to understand how a cell develops the ability to perform divergent functions. Emergence of single cell technologies has provided a unique opportunity to understand this process at a single cell level. Despite the promise, single cell transcriptomic data analysis is full of technical and biological challenges. In this project, we will familiarize ourselves with two main learning goals: reconstruction of regulatory networks and single cell transcriptomic data analysis. We will then apply diverse strategies to infer regulatory networks across different human single cell datasets. We will work in a team to explore different strategies of inferring networks and will evaluate which ones work better. We will aim to summarize the outcome of this project as a small journal article.
Systems biology for adapting salmon breeding and nutrition strategies to modern feedstuffs
Project leader: Jon Olav Vik, Faculty of chemistry, biotechnology and food science, NMBU - Norwegian University of Life Sciences
Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. The Digital Salmon will be an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted whole. See also: The Digital Salmon on YouTube. The participants will investigate the metabolic repertoire of Atlantic salmon fed contrasting diets in a published feed-switch experiment, using a combination of omics data and the constraint-based model SALARECON. This is also a good opportunity to experience FAIR data and model management.
Members of Digital Life Norway Research School will be prioritized for this course. The research school also covers all costs related to travel and accommodation for their members (remember to apply for a ).
After the registration deadline for the course, accepted participants will be notified and receive information about which group project you will work on (based on your wishes).
Scientific matters: Maria Hesjedal, Department of Public Health and Nursing, at the unit for General Practice Research and Medical Ethics, NTNU
Research school matters: Rosalie Zwiggelaar, Research school coordinator, Centre for Digital Life Norway
Miscellaneous: Elisabeth Hyldbakk, Coordinator, Centre for Digital Life Norway