Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- West Virginia University,University of New Mexico
- Organisation type
- Academia,Academia
- Country
- United States of America
- Published
- 11 October 2024
- Authors
- Ádám M. Halász, Srinjoy Das, Stephen L. Mathias, Jeremy S. Edwards
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein-ligand binding affinity prediction
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 1,682,725 tokens
Number of data points ≈ 50,000 unique kinase-ligand affinity pairs Details: - Original data: 80,878 kinase-ligand affinity values - Preprocessed to: 455 kinases × 5,275 ligands matrix with " one in ~180 entries being non-zero." Prediction targets are non zero entries plus sampled negative entries (unclear how many, estimating around 3-5 times the positive) Positive: 455*5275*(1/180)=13334 - Final training data: ~50,000 entries
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- DEEP LEARNING ENABLED DISCOVERY OF KINASE DRUG TARGETS IN PHAROS
- Last updated
- 28 November 2025
What the numbers mean
About this model
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos was published by West Virginia University,University of New Mexico, in United States of America, in October 2024. academia,Academia is the category the publisher falls under.
It works in Biology, and is recorded as doing protein-ligand binding affinity prediction.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
Around 1,682,725 tokens went into training it.
Answers
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos — common questions
What is Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos used for?
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos works in Biology, and is recorded as handling protein-ligand binding affinity prediction. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos?
None. Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos open source?
The licensing for Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos have?
No parameter count has been published for Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos, which is why no memory or speed figure appears on this page.
Who created Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos?
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos was published by West Virginia University,University of New Mexico, based in United States of America, categorised as academia,Academia.
When was Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos released?
Deep Learning Enabled Discovery of Kinase Drug Targets in Pharos was published in October 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.