ChemmineR is a cheminformatics package for analysing drug-like small molecule data in R. In addition, ChemmineR offers visualization functions for compound clustering results and chemical structures. The integration of chemoinformatic tools with the R programming environment has many advantages, such as easy access to a wide spectrum of statistical methods, machine learning algorithms and graphic utilities.
Aim
This 3-day workshop aims to equip participants with the essential skills and knowledge to effectively analyze drug-like small molecules using ChemmineR, a powerful cheminformatics toolkit for R. By the end of the workshop, attendees will proficiently predict physicochemical/structural properties, conduct structural similarity searching, and perform classification and clustering of compound libraries. Furthermore, participants will learn how to utilize visualization functions for interpreting compound clustering results and chemical structures.
What Participants Will Learn
To predict the physicochemical/structural properties, structural similarity searching, classification and clustering of compound libraries
To visualize the functions for compound clustering results and chemical structures.
Structure
Day 1:
Chemical databases and ChemmineR tool
Overview of Chemical Databases
Overview of ChemmineR tool
Day 2:
Bioconductor package
Overview of Bioconductor package
Installation of Bioconductor package
Day 3:
Chemical properties prediction and visualization
Structural properties similarity searching
Molecular visualization
Important Dates
Registration Ends
07:00 PM
Workshop Dates
2024-07-18
08:00 PM onwards
08:00 PM onwards
What You Will Gain
Outcomes
Proficiency in analyzing drug-like small molecules using ChemmineR.
Enhanced understanding of physicochemical properties and structural similarity searching.
Ability to perform classification and clustering of compound libraries.
Competence in visualizing compound clustering results and chemical structures.
Hands-on experience in utilizing ChemmineR for cheminformatics analysis.
Who Should Attend
Graduate degree in Biology, Bioinformatics, Computational Biology, or related fields.
Professionals in the biotechnology, pharmaceutical, or healthcare industries.
Researchers and academics with a focus on molecular biology and structural biology.
Individuals with a keen interest in AI applications in life sciences.
