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- W5a: RNA-seq I Analysis – Measuring gene expressions from RNA-seq data
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- RNA-seq III Analysis – De novo transcriptome assembly using Trinity
- W6: BS-Seq DNA Methylation Analysis with Hoffman2 and R
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- W10: Mathematical Modeling of Cell Signaling
- W11: Metagenomics Analysis with Python and R
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- W14: Intro to Modern Statistics with R
- W15: Bacterial Genomics
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- W26: Protein Structure with AlphaFold
- BS-Sequencing
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- W27: Systems biology of metabolism – workflows and resources for multi-omics data integration
- W28: Advanced Data Visualization w/ ggplot2
- W29: Demultiplexing QC/Good Practices — Hidden Surprises and Illumina Sequencing
- W30: Statistical Methods for Enhancing the Rigor in Single-cell RNA-seq Data Analysis
- W31: Spatial Transcriptomics
- W32: GitHub/Docker
- W33: Accessing The Clinical Database: An Introduction to SQL and the DDR
- W34: Automated Machine Learning
- W35: Advanced Statistics: Regression Models and Statistical Rigor
- W36: Multi-Omics Integration and Network/Pathway Analysis using Mergeomics
- W37: Applications of Large Language Models
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