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2.0.3

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adaMVP-new

Adaptive AI-Augmented Drug Discovery and Development Molecular Vulnerability Picker

Published16 Jan 2026

Direct dependencies7

Transitive dependenciesNot calculated

README

Version 2.0.3 documentation

A3D3a's MVP (adaMVP_new) python package

A novel graph-based, cooperativity-led Markov chain model, A3D3a’s MVP (Adaptive AI-Augmented Drug Discovery and Development Molecular Vulnerability Picker), to identify and prioritize key druggable molecular vulnerabilities in cancer.

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Declared dependencies 7

Native requirements

7 direct targetsNot calculated transitive count

Package / target	Requirement	Relationship
numpy Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`numpy>1.21`	runtime
pandas Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`pandas>1.4`	runtime
matplotlib Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`matplotlib>3.5`	runtime
networkx Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`networkx>2.7`	runtime
tqdm Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`tqdm`	runtime
statsmodels Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`statsmodels>0.13`	runtime
seaborn Environment { "extras": "", "marker": null, "requires_python": ">=3.8", "evaluation": "NOT_EVALUATED" }	`seaborn>0.11`	runtime