enformer-pytorch
importedsoftware/enformer-pytorch
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/lucidrains/enformer-pytorch
- Documentation
- unknown
- Tags
- artificial-intelligence · attention-mechanism · deep-learning · dna-sequences · gene-expression · genomics · transformer
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- Visual-Sequence-Alignment-in-VB6dna-sequences · genomics
This highly visual and responsive VB6 application is an implementation of the global sequence alignment algorithm. It allows the modification of the alignment parameters (match, mismatch, gap), and…
- EEG-Transformerattention-mechanism · transformer
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension…
- clonealigngene-expression
Bayesian inference of clone-specific gene expression estimates by integrating single-cell RNA-seq and single-cell DNA-seq data
- DeepSpotgene-expression
DeepSpot: Deep learning model for predicting spatial transcriptomics from H&E histopathology images. Supports spot-level (Visium) and single-cell (Xenium) resolution.
- DeepSpot2Cellgene-expression
DeepSpot2Cell: Predicting virtual single-cell spatial transcriptomics from H&E images using spot-level supervision
- MERINGUEgene-expression
characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities
- api.github.com/repos/lucidrains/enformer-pytorchretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-06-26, 571 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/57.json→ .entries["enformer-pytorch"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.