Official git repository for Biopython (originally converted from CVS)
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Official git repository for Biopython (originally converted from CVS)
Biomni: a general-purpose biomedical AI agent
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
Making Protein folding accessible to all!
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
A versatile pairwise aligner for genomic and spliced nucleotide sequences
MMseqs2: ultra fast and sensitive search and clustering suite
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena
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.
A Go package for engineering organisms.
Generation of protein sequences and evolutionary alignments via discrete diffusion models
Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
A Practical and Efficient NCBI Taxonomy Toolkit, also supports creating NCBI-style taxdump files for custom taxonomies like GTDB/ICTV
Sequential regulatory activity predictions with deep convolutional neural networks.
The repository host gives no description.
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
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