Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Official git repository for Biopython (originally converted from CVS)
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
Deep probabilistic analysis of single-cell and spatial omics data
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
Generation of protein sequences and evolutionary alignments via discrete diffusion models
Spatial Single Cell Analysis in Python
A tool for semi-automatic cell type classification
Sequential regulatory activity predictions with deep convolutional neural networks.
RNA-seq prediction with deep convolutional neural networks.
Bi-Directional Equivariant Long-Range DNA Sequence Modeling
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