Bioinformatics I (BIO1, next taught autumn 2018): This course covers basic modern molecular biology and algorithms used in bioinformatics research. The course website currently has the course materials from previous years for reference. The site will be updated in autumn 2017.
Bioinformatics II (BIO2, currently running): This builds on Bioinformatics 1, and covers statistical and machine learning approaches in bioinformatics. You can take this course without having done Bio1 if you have a basic understanding of molecular biology. The course website currently has the course materials from previous years for reference.
Neural Information Processing (NIP, currently running): Here Mark van Rossum and myself will cover material at the interface of neuroscience and machine learning. Mark will cover information theory and optimal coding, while my part is about log-linear models of neuronal populations (and moving to neural networks from there). This course is very maths heavy, be prepared to spend time on derivations! See the course website for lectures and relevant materials.
The handout for the PoN (MSc Neuroscience/Neuroinformatics) lecture “Modelling Synaptic Transmission” is availble here. Over several years, this handout has evolved into a rather comprehensive review, and I will cover only things I deem most interesting (which change every year). Please let me know if there are mistakes or important omissions - this handout is constantly improved and extended, and may even be published as a review one day. Update 27. Apr 2013: the review is out now!
VLSI Electrophysiology: For teaching purposes, I have developed software for Tobi Delbrueck’s VLSI retina chip to visualise spike data and create PSTH’s. More information is here. More recently we have also used Tobi’s DVS chip to demonstrate how our retina functions. I’d be keen to hear about similar projects elsewhere.
Potential Students: I’m happy to supervise UG4, MSc and PhD projects in computational neuroscience, please contact me (best with ideas) if you are interested.