Скачать с ютуб GeneSelectR: how to identify relevant features in RNA sequencing datasets в хорошем качестве

GeneSelectR: how to identify relevant features in RNA sequencing datasets

What you will discover: GeneSelectR, an open-source R package that innovatively combines ML and bioinformatic data mining approaches for enhanced feature selection during High-dimensional Bulk RNA sequencing. You are: a bioinformatician who performs bulk RNAseq analysis but struggles with batch effects Speaker: Damir Zhakparov, a PhD candidate in Katja Baerenfaller’s group based in Swiss Institute of Allergy and Asthma Research (SIAF) in Davos. Click to access specific sections of the talk: - 00:45 Differential gene expression analysis limitations - 02:06 But machin learning (ML) is not a clear-cut solution - 03:24 GeneSelectR: A user-friendly R package workflow - 06:22 Package Features - 09:21 Availability and tutorials Reference papers and resource - GeneSelectR: An R Package Workflow for Enhanced Feature Selection from RNA Sequencing Data View ORCID ProfileDamir Zhakparov, Kathleen Moriarty, Damian Roqueiro, Katja Baerenfaller DOI: https://doi.org/10.1101/2024.01.22.57... - https://CRAN.R-project.org/package=Ge... - https://github.com/dzhakparov/GeneSel... Any questions about this talk? Contact damir.zhakparov[at]uzh.ch More about the speaker: Damir Zhakparov is a PhD candidate in Katja Baerenfaller’s group based in Swiss Institute of Allergy and Asthma Research (SIAF) in Davos. In 2020, he obtained his Master’s degree in High-throughput Biotechnology in École supérieure de biotechnologie de Strasbourg, France. Throughout his PhD he was involved in a wide variety of projects ranging from clinical data analysis to wastewater SARS-CoV-2 surveillance. His primary research interests are transcriptomic data analysis, Machine Learning applied to tabular data and software development. Read the news: https://www.sib.swiss/in-silico-talks...