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VAERHNN

imported

therapeutics/vaerhnn

Voting-averaged ensemble regression and hybrid neural networks to investigate potent leads against colorectal cancer

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

VAERHNN project image
GitHub preview card for gxCaesar/VAERHNN. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Therapeutics
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
cancer · deep-learning · drug-discovery · drug-repurposing · drug-target-interactions
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.

  • DeepDrugDomaindrug-discovery · drug-repurposing · drug-target-interactions

    DeepDrugDomain: A versatile Python toolkit for streamlined preprocessing and accurate prediction of drug-target interactions and binding affinities, leveraging deep learning for advancing…

  • ISCMFdrug-discovery · drug-repurposing · drug-target-interactions

    ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction

  • BarlowDTIdrug-discovery · drug-target-interactions

    Accurate prediction of drug–target interactions in drug discovery.

  • BindingAffinitydrug-discovery · drug-target-interactions

    Exploring deep learning for predicting the binding affinity between a small molecule (i.e. a drug) and a protein.

  • CompassDockdrug-discovery · drug-target-interactions

    Official Implementation of CompassDock

  • DrugGENdrug-discovery · drug-target-interactions

    Official implementation of DrugGEN: Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks

sources
  1. api.github.com/repos/gxCaesar/VAERHNN
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2022-04-16, 6 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/45.json→ .entries["vaerhnn"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.