Code for running RFdiffusion
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This package contains deep learning models and related scripts for RoseTTAFold
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
- kmer
- dnabert-model
- kmer-format
- gpu
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
Spatial Single Cell Analysis in Python
- single-cell-rna-seq
- single-cell-genomics
- spatial-transcriptomics
- spatial-analysis
Generative biopolymer design with rich conditioning.
A tool for semi-automatic cell type classification
- python
- single-cell
- machine-learning
- scrna-seq
Sequential regulatory activity predictions with deep convolutional neural networks.
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
Schema and generated objects for biolink data model and upper ontology
- biolink
- monarchinitiative
- gene-ontology
- datamodel
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
Open-source software for exploring and analyzing large, high-dimensional image-derived data.
- cellprofiler-analyst
- cellprofiler
- image-analysis
- machine-learning
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
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
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
- analysis
- claude
- claudecode
- dna
Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
- bioinformatics
- cell-type-deconvolution
- computational-biology
- deconvolution
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning