Open source tumor evidence matching for sequencing labs and hospitals without molecular tumor boards. Research prototype; oncologist review required.
- bioinformatics
- cancer-research
- computational-biology
- drug-repurposing
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Open source tumor evidence matching for sequencing labs and hospitals without molecular tumor boards. Research prototype; oncologist review required.
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
🏃 The go-to single-cell Foundation Model
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
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Python package for image-based profiling
OCaml Bioinformatics Library
Learning cell communication from spatial graphs of cells
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
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Toolbox for the analysis of smFISH images.
TypeDB Bio: Biomedical Knowledge Graph
BulkFormer: A large-scale foundation model for human bulk transcriptomes
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
The framework for quantification of neuronal anatomy
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Tool for precise, interactive, fast and scalable FISH spot detection
Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
MCP server for spatial transcriptomics analysis through natural language interfaces.
Predicting Cell Health with Morphological Profiles
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer