This is the repository for the course CBM101: Introduction to Computational Biomedicine and Machine Learning, a collaboration within the NordBiomed network.
Here you find code and documentation for the course. You will find more information about the Summer school testing this course at https://nordbiomed.org/news/summer-school-2019-computational-biomedicine (e-learning modules will later be avaialble on the Open edX platform at Bibsys).
Follow the instructions at Setting up your system to get ready
Note: To access the course notebooks interactively without downloading any software we are planning to use Binder
The course is based on the Jupyter Notebook, a web-based framework for developing and presenting code-based projects (take a look at https://youtu.be/HW29067qVWk og https://youtu.be/2eCHD6f_phE for introductions to Jupyter Notebooks).
Throughout the course you will work with notebooks that contain various material and programming tasks. We recommend that you make a copy of our notebooks before you are editing them. In this respect you might adopt the naming convention my_[name_of_notebook].ipynb.
- Python, Numpy, Pandas, Matplotlib, Nibabel, Biopython and more: run through this notebook to check that your environment is OK.
CBM101 is part of the "Open Educational Resources in Computational Biomedicine"* (OERCompBiomed) project conducted by the NordBioMed.org and funded by Erasmus+.
NordBioMed is a collaborative network in the field of Biomedicine(*) between the Universities of Turku, Eastern Finland (Kuopio), Bergen, Odense and Karolinska Institutet. The network was originally formed in 2013 to strengthen the individual biomedical teaching programs within the component universities and make them internationally more competitive by providing complementary activities from the partner universities. The network supports both student and teacher mobility, organises intensive courses and develops virtual online teaching and an information platform on the Open edX platform, supported by a GitHub repository. Links that redirects to the study programme pages of each NordBioMed partner universities can be found here.
(*) Biomedicine covers those areas of human biology, chemistry and medicine that seek to explain the factors behind health and disease at the molecular and cellular level. This information is applied in the development of better diagnostics and treatments.
The Nordic network of Biomedicine educators NordBioMedNet has received a grant of 350 000 euros from Erasmus+ to develop biomedicine education. With the received money the network can start providing Open Educational Resource (OER) courses that are open for everybody. They will start by providing courses of Biomedical Ethics, Digital Pathology, Computational Biomedicine and machine learning.
The main objective of the project is to provide students in the field of biomedicine with modern, timely, up-to-date, and professionally relevant learning experiences that enable them to develop skills and competences in biomedical data management and use, and skills and competences to identify, analyse and handle ethical challenges within modern biomedicine.
As modern biomedical research produces massive data generated by high-throughput methods, students need to develop computational and analytical skills to manage and utilise “big data”. Moreover, knowledge and tools in bioethics are also increasingly important due to present rapid technological development in biomedicine with, for example, a new era of modern genomic/genetic research ripe with very critical and difficult ethical issues.
You can read more about OER in this Foundations for OER Strategy Development document.
Major topics in the "Introduction to Computational Biomedicine and Machine Learning" part of OERCompBiomed project are:
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Tools (Python, R & friends) & Data retrieval (see also https://computingskillsforbiologists.com)
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Complex network analysis
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Unsupervised learning
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Supervised learning
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Deep learning
-- “Hello World” (UiB) + DeepCLIP (SDU) + DeepBind (UEF)