Bioinformatics & Genomics: From Data Analysis to AI Applications
When
Enhance your knowledge of sequence manipulation for sequencing data preparation; improve your alignment skills using various tools; and understand the assessment of alignment quality.
This workshop provides graduate students in public universities with the necessary skills and tools to analyze biological data using high-performance computing resources.
Participants will acquire hands-on experience with industry-standard command-line tools (CLI) for DNA and RNA sequencing analysis, sequence manipulation and alignment, and pipeline management for automating complex workflows. They will also learn about differential expression analysis for identifying genes with altered expression levels, data visualization techniques for effectively presenting results, and the basics of artificial intelligence (AI) and machine learning (ML) in bioinformatics.
Upon completion of this workshop, graduates will be capable of using these powerful tools and methods to address real-world biological challenges and make significant contributions to bioinformatics research.
Required Skills
| Skill | Description |
|---|---|
| Basic understanding of biology | This workshop assumes a basic understanding of biological concepts, such as DNA, RNA, genes, and genomes. |
| Familiarity with the command line (optional, but helpful) | While not required, familiarity with the command line will help navigate the tools covered in the workshop. |
| Enthusiasm for learning new computational skills | A strong interest in learning new computational skills is essential for success in this workshop. |
SERIES: Bioinformatics & Genomics: From Data Analysis to AI Applications
Where: REGISTER for Zoom link Weaver Science-Engineering Library, Rm 212 and on Zoom
Instructor: Michele Cosi
YouTube: UArizona DataLab and session links
Workshop sessions:
- 1/30 Sequence manipulation, alignment, and assessment
- 2/6 A Beginner's Guide to RNA-seq with DESeq2
- 2/13 RNA-Seq Data Analysis in R: From Raw Counts to Differential Expression Analysis
- 2/20 Downstream Analysis of RNA-Seq Results in R: GSEA, PPI Networks, and Biological Interpretation
- 2/27 QTL mapping with qtl2
- 3/6 Introduction to GWAS
- 3/20 De-novo Detection and Annotation of Transposable Elements
- 3/27 Explore Current AI/ML Trends and Tools in Bioinformatics