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Course description: Deep Learning for genomic sequence and biological-image analysis. This interactive workshop will teach the use of machine learning techniques (convolutional and recurrent neural networks) for the analysis of genomic sequences and biological images. The course's target audience is the public interested in bioinformatics who want to learn the use of these novel techniques. No prior machine learning or biological knowledge is necessary. The course will combine recorded presentations and interactive online practical exercises in Python.


Target group: public interested in bioinformatics


Each of the 6 parts is approximately 26.33 minutes of theory (slides and voiceover) followed by a demonstration and time for the viewer to Pause and try the demonstration for themselves using the online resources provided.

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Faculty of Science

Deep Learning for genomic sequence and biological image analysis.

https://is.muni.cz/ekurzy/CEIT_BIT_2 Copy link to clipboard

6 lessons
2.67 hours total
free
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If you already are a student of the e-course, please log in to the IS MU.
Registration is open from 14/2/2022

Lecturers

Panagiotis Alexiou, PhD
241340@mail.muni.cz
Mgr. David Čechák
433774@mail.muni.cz

E-course syllabus

  • Part I: Building a Deep Learning Model

  • I. Introduction and Neurons

  • II. Neural Networks

  • Part II: Deep Learning for Image Recognition

  • I. Convolutional Neural Networks

  • II. Transfer Learning

  • Part III: Deep Learning for Sequential Data

  • I. Tokenization, Numericalization

  • II. Recurrent Neural Networks


More about the e-course