A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists

Rabea Müller, Akinyemi Mandela Fasemore, Muhammad Elhossary, Konrad U. Förstner
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:68-72, 2022.

Abstract

Machine Learning represents an invaluable set of tools for the analysis of data in molecular biology as well as bio-medicine. Here we present an training approach to teach fundamental machine learning skills to researchers in their early career stage (PhD and postdoc level) with the aim to empower them to apply these methods in their own research projects. The content was developed for being delivered in a short and intense learning period as part of a remote systems biology workshop but can be adapted to other scenarios with a less restricted time frame.

Cite this Paper

BibTeX
@InProceedings{pmlr-v170-muller22a, title = {A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists}, author = {M\"uller, Rabea and Fasemore, Akinyemi Mandela and Elhossary, Muhammad and F\"orstner, Konrad U.}, booktitle = {Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop}, pages = {68--72}, year = {2022}, editor = {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver}, volume = {170}, series = {Proceedings of Machine Learning Research}, month = {08--13 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v170/muller22a/muller22a.pdf}, url = {https://proceedings.mlr.press/v170/muller22a.html}, abstract = {Machine Learning represents an invaluable set of tools for the analysis of data in molecular biology as well as bio-medicine. Here we present an training approach to teach fundamental machine learning skills to researchers in their early career stage (PhD and postdoc level) with the aim to empower them to apply these methods in their own research projects. The content was developed for being delivered in a short and intense learning period as part of a remote systems biology workshop but can be adapted to other scenarios with a less restricted time frame.} }
Endnote
%0 Conference Paper %T A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists %A Rabea Müller %A Akinyemi Mandela Fasemore %A Muhammad Elhossary %A Konrad U. Förstner %B Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop %C Proceedings of Machine Learning Research %D 2022 %E Katherine M. Kinnaird %E Peter Steinbach %E Oliver Guhr %F pmlr-v170-muller22a %I PMLR %P 68--72 %U https://proceedings.mlr.press/v170/muller22a.html %V 170 %X Machine Learning represents an invaluable set of tools for the analysis of data in molecular biology as well as bio-medicine. Here we present an training approach to teach fundamental machine learning skills to researchers in their early career stage (PhD and postdoc level) with the aim to empower them to apply these methods in their own research projects. The content was developed for being delivered in a short and intense learning period as part of a remote systems biology workshop but can be adapted to other scenarios with a less restricted time frame.
APA
Müller, R., Fasemore, A.M., Elhossary, M. & Förstner, K.U.. (2022). A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists. Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 170:68-72 Available from https://proceedings.mlr.press/v170/muller22a.html.

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