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INCF-HBP Short Course on Fundamentals of Ontology engineering
Curious about how you can exploit ontologies to standardize your metadata and embed your research in the semantic web? Join the INCF-HBP short course Fundamentals of Ontology Engineering.
Course dates: January 28th - 29th 2019
Course location: University of Oslo, Norway
Course description and admission
Fundamentals of Ontology engineering
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Neuroscience data integration through use of digital brain atlases
Identification of anatomical location is fundamental to interpretation and comparison of neuroscience data. Assignment of location to brain image data and data integration is facilitated by new 3-D brain atlas resources.
This course gives an introduction to currently available reference atlases for mouse, rat, and human brain. It will demonstrate how the 3D brain templates for the reference atlases are acquired, how they are used as a basis for delineating the structures of the brain, how they can be enriched by other data modalities, and how they can be used as a basis for assigning location (coordinate based or semantic) to a wide range of structural and functional data collected from the brain.
The course will also exemplify the use of a data system for organizing and analyzing neuroscience data collections in the context of reference atlases.
Course description and admission
IMB9345 – Neuroscience data integration through use of digital brain atlases
This course was held in 2018 and 2019. In 2020, the course was cancelled due to Covid-19.
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Computational Neuroscience (Master Course)
Course contents:
Selected topics related to mathematical modelling of (i) signal processing in nerve cells, (ii) neural coding and decoding, (iii) receptive fields in the visual system, (iv) information transmission in the nervous system, (v) biophysics of nerve cells, (vi) biological neural networks, and (vii) learning and memory.
Course description and admission:
https://www.nmbu.no/course/FYS388
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Computational Neuroscience (Phd Course)
Course contents:
Selected topics related to mathematical modelling of (i) signal processing in nerve cells, (ii) neural coding and decoding, (iii) receptive fields in the visual system, (iv) information transmission in the nervous system, (v) biophysics of nerve cells, (vi) biological neural networks, and (vii) learning and memory.
Course description and admission: