This package contains deep learning models and related scripts for RoseTTAFold
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Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
Foundation Models for Genomics & Transcriptomics
Spatial Single Cell Analysis in Python
- single-cell-rna-seq
- single-cell-genomics
- spatial-transcriptomics
- spatial-analysis
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
- dataset
- dna
- dna-processing
- dna-training
Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
- cancer-genomics
- cnv-detection
- single-cell
- phylogeny
Probabilistic cell segmentation for in situ spatial transcriptomics
Data visualisation web components for the life sciences.
- biohackeu21
- bioinformatics
- visualization
- webcomponents
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.