The analysis of imaging datasets is both exciting and challenging. New and increasingly powerful techniques try to maximize the information derived from multi-dimensional imaging datasets. Yet, every dataset can be […]
The goal of the workshop is to enable the participants to submit and rationally evaluate results of the AlphaFold protein structure predictions. The class will cover the basic principles of […]
Spatial transcriptomics is an emerging field that bridges molecular biology and anatomy. Over the last decade, a battery of assays have been developed that profile gene expression in-situ, i.e, measuring […]
This 3-day interactive workshop introduces the overarching principles guiding generative modeling and specifically Large-Scale Language Models (LLM), their application in Python for inference, and specific use-cases in Genomics. Experience with […]
"Learning cellular organization and function across scales"
RNA-seq I aims to provide an introduction and the basics tools to process raw RNA-seq data on a cluster machine (Hoffman2). The workshop can serve also as a starting point […]
RNA-seq II aims to provide tools for analysis of gene expression data from read counts to biology using R. To facilitate learning, the workshop will use a real case study […]
"Deep learning models for genomics and epigenomics"
This workshop aims to introduce the basic concepts and algorithms for single-cell RNA-seq analysis. It will help participants obtain a better idea of how to use scRNA-seq technology, from considerations […]
