Summer 2025

Scientific Reproducibility with Containers

July 7 and 8, 2025
9 AM to 5 PM both days
G9.102

The nanocourse emphasizes reproducibility in scientific research using software containers, which enable reliable sharing and execution of computational tools. Participants will receive hands-on training in container fundamentals, Git and GitLab for development, and scientific workflows using Astrocyte. The course also covers building advanced machine learning applications in a portable way. Hands-on exercises will focus on container operations, containerized development, and workflow creation on BioHPC.

This two-day workshop will provide comprehensive instruction and hands-on training in various topics including:

  • Fundamentals of Containers - what they are, how to use them, and how to create them.

  • Git and GitLab as tools to streamline the development of containers.

  • Scientific workflows using Astrocyte. Aimed at bioinformaticians, this segment introduces the structure of Astrocyte packages, Nextflow as a workflow language, and other related concepts.

  • Building advanced machine learning applications in a simple and portable way.

Participants will engage in hands-on exercises covering container operations on BioHPC, developing containers using Git and GitLab, and crafting Astrocyte pipelines using containers. 

Pre-requisites: Familiarity with BioHPC usage and a fundamental understanding of Linux.

Registration opens in May.

For UTSW graduate students and PostDocs, academic credit (1 credit hour) is available.
Graduate Students: BME 5096-02 Special Topics: Scientific Reproducibility using Containers for Summer 2025.
PostDocs: PDRT 5095-01 Special Topics: Scientific Reproducibility using Containers for Summer 2025.

Course Director: Liqiang Wang

Instructors: BioHPC Team

Basic Optics for Microscopy

July 25, 2025
Time TBD
ND11 - microscopy rooms

This half-day / one-day workshop offers hands-on basic optics experiments, which is the foundation for building a (fluorescence) microscope or other optics instruments. We will design a few optics experiments and the participants will learn some basic knowledge of optics, such as walking the beams, making a collimating beam, creating a clear Gaussian beam, and aligning an optical train.

Prerequisites: None.

Registration opens in May.
There is no academic credit for this nanocourse. A certificate will be issued if requested after successful completion.

Course Director: Bo-Jui Chang, PhD

Shiny Apps for Interactive Data Analysis and Sharing

August 4 and 5, 2025
9 AM to 5 PM both days
G9.102

Shiny is a framework for developing interactive applications that run R code (or python). These apps are broadly useful in biological data analysis and are particularly well suited for exploratory analysis of complex data, sharing datasets and workflows with non-coding users, and interactive teaching demonstrations. In this nanocourse, students will learn to quickly write simple Shiny apps and share them with users. Students will independently develop their own applications and present them at the end of the course. Basic R competency is required, because instruction will take place in R. Python may be supported if there is interest.

Prerequisites: Fluency with R programming language.

Registration will open in June.
For UTSW graduate students and PostDocs, academic credit (1 credit hour) is available.
Graduate Students: BME 5096-03 Special Topics: Shiny Apps for Integrated Data Analysis for Summer 2025.
PostDocs: Since this credit hour will be retro-awarded in Fall 2025, the course number in Fall 2025 will be applied.

Course Director: Scott Saunders, PhD, Ermis-loannis Michail-Delopoulos, MS

Scalable Data Analysis with Dask

August 6, 2025
9 AM to 5 PM
ND11.218

This one-day nanocourse offers a concise introduction to large-scale parallel data processing in Python using Dask. Participants will learn practical techniques for running computationally intensive data analyses in a multi-node, distributed environment.

Prerequisites: Advanced Python knowledge is required.

Registration opens in June.
For UTSW graduate students and PostDocs, academic credit (1 credit hour) is available. This credit will be retro-awarded in the Fall 2025 semester.
Graduate Students: BME 5096-04 Special Topics: Scalable Data Analysis with Dask for Summer 2025.
PostDocs: Since this credit hour will be retro-awarded in Fall 2025, the course number in Fall 2025 will be applied.

Course Director: Kevin Dean, PhD

Instructors: TBD