PROTON

Graph AI generates neurological hypotheses validated in molecular, organoid, and clinical systems.

Introduction

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Figure-2 — We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions.

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Figure-2 — We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions.

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Multi-disease evaluations

ParkinsonBipolar DisorderAlzheimer's Disease

Parkinson

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Figure-2 — We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions.

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Bipolar Disorder

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Figure-2 — We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions.

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Alzheimer's Disease

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Figure-2 — We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions.

Neurological diseases are the leading global cause of disability, yet most lack disease-modifying treatments. To help address this gap, we developed PROTON, a graph AI model that generates hypotheses for neurological disease.

We demonstrate diverse disease-specific applications of PROTON using experimental and clinical data in three neurological conditions: Parkinson's disease (PD), bipolar disorder (BD), and Alzheimer's disease (AD). PROTON nominates candidate drugs, forecasts drug approvals, prioritizes pesticides, and identifies genetic, proteomic, and protein–protein interaction links across multiple biological scales.

Licence

PROTON is released under the MIT License, If you use PROTON, please cite.

@article{
	noori_graph_2025,
	title={Graph AI generates neurological hypotheses validated in molecular, organoid, and clinical systems},
	author={Noori, Ayush and Polonuer, Joaquin and Meyer, Katharina and Budnik, Bogdan and Morton, Shad and Wang, Xinyuan and Nazeem, Sumaiya and He, Yingnan and Arango, Iñaki and Vittor, Lucas and Woodworth, Matthew and Krolewski, Richard C. and Li, Michelle M. and Liu, Ninning and Kamath, Tushar and Macosko, Evan and Ritter, Dylan and Afroz, Jalwa and Henderson, Alexander B. H. and Studer, Lorenz and Rodriques, Samuel G. and White, Andrew and Dagan, Noa and Clifton, David A. and Church, George M. and Das, Sudeshna and Tam, Jenny M. and Khurana, Vikram and Zitnik, Marinka},
	journal={arXiv preprint},
	note={arXiv:XXXX.XXXXX (placeholder)},
	year={2025}
}

Team

Ayush Noori

example@email.com

Sudeshna Das

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Jenny M. Tam

jenny-tam.webp

Vikram Khurana

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Marinka Zitnik

example@email.com