Starred repositories
scFOCAL operates through the integration of drug-response transcriptional consensus signatures (TCSs) derived from the LINCS L1000 dataset with multi-subject single-cell RNA sequencing data, and fa…
2026年6月更新，目前国内可用Docker镜像源汇总，DockerHub国内镜像加速列表，🚀DockerHub镜像加速器
Partial/differential file download client over HTTP(S)
AetherCell is a hierarchical generative framework designed to predict context-specific transcriptomic responses to drugs and genetic perturbations. By bridging high-resolution RNA-seq contexts with…
CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.
The integration of single cell rank-based gene set enrichment analysis
Information of public available data sets for biomechanics.
Code used to benchmark Xenium
rapids-singlecell: GPU-accelerated framework for scRNA analysis
A unified framework for predicting drug-target interactions, binding affinities and activation/inhibition mechanisms.
A visible neural network model for drug response prediction
Machine learning-based integration model with elegant performance
Methods to discover gene programs on single-cell data
A tool for semi-automatic cell type classification
LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-prompt…
Analysis of Single Cell Expression data in Julia
CanSig: a package to compare methods for discovering shared transcriptional states in cancer.
Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq and Spatial Transcriptomics data.
An R package for drug response prediction and drug-gene association prediction.
Portable file server with accelerated resumable uploads, dedup, WebDAV, SFTP, FTP, TFTP, zeroconf, media indexer, thumbnails++ all in one file
Tutorials for the Monod package, which fits CME models to sequencing data.