Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
- cancer-genomics
- cnv-detection
- single-cell
- phylogeny
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Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
talk with NCBI entrez using R
A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.
Probabilistic cell segmentation for in situ spatial transcriptomics
scPerturb: A resource and a python/R tool for single-cell perturbation data
Open source tumor evidence matching for sequencing labs and hospitals without molecular tumor boards. Research prototype; oncologist review required.
PhyloNetworks: a julia package with utilities for phylogenetic networks
Open-source software for exploring and analyzing large, high-dimensional image-derived data.
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
🏃 The go-to single-cell Foundation Model
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
Interpretable bilinear attention network with domain adaptation improves drug-target prediction.
Data visualisation web components for the life sciences.
Accurate and efficient spot detection for microscopy data
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
The repository host gives no description.
A tool for cell instance aware segmentation in densely packed 3D volumetric images
GeneCompass
Learning cell communication from spatial graphs of cells
code to run sei and obtain sei and sequence class predictions
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Rails frontend to The Genome Institute's drug gene interaction database.
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.