ML and data mining approaches for downstream analyses
GeneSelectR: how to identify relevant features in RNA sequencing datasets
High-dimensional Bulk RNA sequencing (RNAseq) datasets pose a considerable challenge in identifying biologically relevant features for downstream analyses and data mining efforts. Introducing GeneSelectR, an open-source R package that innovatively combines ML and bioinformatic data mining approaches for enhanced feature selection.
In this video, you will also see how you can use GeneSelectR to select features from a normalized RNAseq dataset with a variety of ML methods and user-defined parameters. If you are a bioinformatician who performs bulk RNAseq analysis but struggles with selecting a gene list for downstream analyses, then this talk is for you!
About the in silico talks series – The latest in bioinformatics by SIB Scientists
The in silico talks online series aims to inform bioinformaticians, life scientists and clinicians about the latest advances led by SIB Scientists on a wide range of topics in bioinformatics methods, research and resources. Stay abreast of the latest developments, get exclusive insights into recent papers, and discover how these advances might help you in your work or research, by subscribing to the in silico talks mailing list.
