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Target2DeNovoDrugPropMax : a novel programmatic tool incorporating deep learning and in silico methods for automated de novo drug design for any target of interest

机译：target2denovodrugpropmax：一种新型的编程工具，包括深入学习和Silico方法，用于自动de novo药物设计，以获得任何感兴趣的目标

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Rafal Madaj; Ben Geoffrey; Akhil Sanker; Pavan Preetham Valluri;
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1. Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases [J] . Ahmet Sureyya Rifaioglu, Heval Atas, Maria Jesus Martin, Briefings in bioinformatics . 2019,第5期

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2. Changing Paradigm from one Target one Ligand Towards Multi-target Directed Ligand Design for Key Drug Targets of Alzheimer Disease: An Important Role of In Silico Methods in Multi-target Directed Ligands Design [J] . Akhil Kumar, Ashish Tiwari, Ashok Sharma Current neuropharmacology . 2018,第6期

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3. From in silico target prediction to multi-target drug design: current databases, methods and applications. [J] . Koutsoukas A, Simms B, Kirchmair J, Journal of proteomics . 2011,第12期

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4. Comparative Studies On Drug-Target Interaction Prediction Using Machine Learning and Deep Learning Methods With Different Molecular Descriptors [C] . Haswani Ismail, Nurul Hashimah Ahamed Hassain Malim, Siti Zuraidah Mohamad Zobir, International Conference of Women in Data Science at Taif University . 2021

机译：用机器学习和不同分子描述符的深层学习方法对比较研究
5. Targeting Disease With A New De Novo Protein Design Framework For Drug Discovery. [D] . Peterson, Meghan Bellows. 2011

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6. Recent applications of deep learning and machine intelligence on in silico drug discovery: methods tools and databases [O] . Ahmet Sureyya Rifaioglu, Heval Atas, Maria Jesus Martin, -1

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7. A programmatic tool for automatic ease in coronavirus drug discovery through programmatically automated data mining, QSAR and In Silico modelling [O] . Ben Geoffrey A S, Rafal Madaj, Akhil Sanker, 2020

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Target2DeNovoDrugPropMax : a novel programmatic tool incorporating deep learning and in silico methods for automated de novo drug design for any target of interest

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