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DISC

imported

software/disc

A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

Machine-generated from the listed sources and not yet reviewed by a human.

DISC project image
GitHub preview card for iyhaoo/DISC. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
deep-learning · imputation · semi-supervised-learning · single-cell · transcriptome
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • LR-splitpipesingle-cell · transcriptome

    Demultiplexing and debarcoding tool designed for LR-Split-seq data.

  • scCATCHsingle-cell · transcriptome

    Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data

  • TrendCatchersingle-cell · transcriptome

    TrendCatcher is an open source R-package that allows users to systematically analyze and visualize time course data. Please cite "Temporal transcriptomic analysis using TrendCatcher identifies early…

  • sisuasemi-supervised-learning · single-cell

    SemI-SUpervised generative Autoencoder models for single cell data

  • mavistranscriptome

    Merging, Annotation, Validation, and Illustration of Structural variants

  • RATTLEtranscriptome

    Reference-free reconstruction and error correction of transcriptomes from Nanopore long-read sequencing

sources
  1. api.github.com/repos/iyhaoo/DISC
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2021-05-19, 12 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/12.json→ .entries["disc"]

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