openmedical/registry
← registry

MRBDTA

imported

therapeutics/mrbdta

Predicting drug–target binding affinity through molecule representation block based on multi-head attention and skip connection

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

MRBDTA project image
GitHub preview card for LiZhang30/MRBDTA. 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
drug-discovery
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.

  • 50_layer_Resnetdrug-discovery

    50 Layer Resnet to predict the regression values of Tetrahymena pyriformis IGC50 from 2d molecular images only

  • AAVGendrug-discovery

    Protein Language model for AAV capsid generation.

  • ablanxdrug-discovery

    JAX/Flax port of AbLang2's AbRep encoder: differentiable antibody language-model embeddings and per-block attention, loading the original weights unchanged.

  • Academiadrug-discovery

    Este repositorio debe ser el punto de partida y encuentro para cualquier investigador o estudiante que quiera comenzar a trabajar con/en la UIBCDF. Si has caído aquí por otro motivo y este material…

  • AD-scRNA2QSARdrug-discovery

    A comprehensive computational pipeline that bridges single-cell genomics and cheminformatics to accelerate Alzheimer's Disease research. This project integrates advanced bioinformatics and machine…

  • admetMesh-Botdrug-discovery

    :robot: Use GitHub Actions and admetMesh to predict admet automatically per 30 minutes.

sources
  1. api.github.com/repos/LiZhang30/MRBDTA
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2025-01-19, 8 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/55.json→ .entries["mrbdta"]

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