Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
Repository Index
47,133 repositories indexed
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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
- self-attention
- compound-protein-interaction
- transformercpi
- structure-free-virtual-sreening
Interpretable bilinear attention network with domain adaptation improves drug-target prediction.
Data visualisation web components for the life sciences.
- biohackeu21
- bioinformatics
- visualization
- webcomponents
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
- protein
- protein-sequences
- protein-design
- representation-learning
A tool for cell instance aware segmentation in densely packed 3D volumetric images
- segmentation
- deep-learning
- bioinformatics
- neural-network
Learning cell communication from spatial graphs of cells
- tensorflow
- gnn
- glm
- cvae
code to run sei and obtain sei and sequence class predictions
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Structural variant detection and association testing
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.
Toolbox for the analysis of smFISH images.
- pattern-classification
- rna-localization
- segmentation
- smfish
BulkFormer: A large-scale foundation model for human bulk transcriptomes
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
- r
- neuroanatomy-toolbox
- cran
- neuron
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
- epigenomics
- pattern-search
- data-visualization
- interactive-machine-learning
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
- foundation-models
- gpt
- single-cell
The framework for quantification of neuronal anatomy
- neuroscience
- neuroanatomy-toolbox
- imagej
- imagej2
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
- analysis
- claude
- claudecode
- dna
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations