In this Master's thesis, the graph properties of a multi-level drug-protein network are studied, as well as how the network's shape has informed discoveries over the years, identifying primarily crawling discoveries and a smaller number of hopping discoveries. Finally, the network structure is used to inform a network diffusion recommendation system and to prioritize existing drugs for repurposing against proteins in organisms that cause Neglected Tropical Diseases.
Heter-LP: A heterogeneous label propagation algorithm and its application in drug repositioning
Isfahan University of Technology（伊斯法罕理工大学）；Amirkabir University of Technology（阿米尔卡比尔理工大学）；Isfahan University of Medical Sciences（伊斯法罕医科大学）；Carleton University（卡尔顿大学）
BVSIMC: Bayesian Variable Selection-Guided Inductive Matrix Completion for Improved and Interpretable Drug Discovery
Department of Statistics University of South Carolina（统计学系南卡罗来纳大学）；Department of Biostatistics University of South Carolina（生物统计学系南卡罗来纳大学）；Department of Biostatistics University of Florida（生物统计学系佛罗里达大学）；Department of Surgery University of Florida（外科医学系佛罗里达大学）；Department of Statistics George Mason University（统计学系乔治·梅森大学）
SOC-DGL: Social Interaction Behavior Inspired Dual Graph Learning Framework for Drug-Target Interaction Identification
College of Marine Electrical Engineering, Dalian Maritime University（大连海事大学海洋电气工程学院）；AI thrust, Information Hub, Hong Kong University of Science and Technology (GuangZhou)（香港科技大学（广州）人工智能方向、信息中心）；School of Artificial Intelligence and Computer Science, Jiangnan University（江南大学人工智能与计算机科学学院）；Department of Information Science and Technology, Dalian Maritime University（大连海事大学信息科学与技术学院）
SAveRUNNER: a network-based algorithm for drug repurposing and its application to COVID-19
新型人类冠状病毒COVID-19/SARS-CoV-2的新颖性以及缺乏有效的药物和疫苗，导致采用各种各样的策略来对抗这一全球大流行病。这些策略中的许多依赖于现有药物的重新定位，与从头药物发现相比，这可以缩短时间并降低成本。在这项研究中，我们提出了一种新的基于网络的药物重新定位算法，称为SAveRUNNER（Searching off-lAbel dRUg aNd NEtwoRk），它通过一种新的基于网络的相似性度量来量化药物靶标和人类相互作用组中疾病特异性蛋白质之间的相互作用，从而预测药物-疾病关联，该相似性度量优先考虑位于相同网络邻域中的药物和疾病之间的关联。具体而言，我们将SAveRUNNER应用于14种选定疾病的小组，这些疾病具有关于其致病基因的综合知识，并且已发现与COVID-19相关的遗传相似性，共病或与暂时重新用于治疗COVID-19的药物的关联。特别关注SARS子网络，我们确定了282种可重复使用的药物，包括一些最有传言的COVID-19治疗标签外药物，以及实际用于临床实践的5种药物的新组合疗法。此外，为了最大限度地提高推定的下游验证实验的效率，我们根据其基于网络的相似性值优先考虑了24种潜在的抗SARS-CoV可再利用药物。这些排名靠前的药物包括ACE抑制剂、单克隆抗体和凝血酶抑制剂。最后，我们的研究结果通过基因集富集分析进行了计算机验证，证实了大多数网络预测的可重…
GastroDL-Fusion: A Dual-Modal Deep Learning Framework Integrating Protein-Ligand Complexes and Gene Sequences for Gastrointestinal Disease Drug Discovery
Technical University of Munich（慕尼黑工业大学）；University of Michigan（密歇根大学）；Georgia Institute of Technology（佐治亚理工学院）
DrugReason: Dynamic Multi-View Reasoning over Knowledge Graph and Language Evidence for Drug Repurposing
University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；Stevens Institute of Technology（史蒂文斯理工学院）；Emory University（埃默里大学）；Massachusetts Institute of Technology（麻省理工学院）
DrugGen 2: A disease-aware language model for enhancing drug discovery
Regenerative Medicine Research Center（再生医学研究中心）；Isfahan University of Medical Sciences（伊斯法罕医科大学）；Isfahan Neuroscience Research Center（伊斯法罕神经科学研究中心）；School of Pharmacy（药学院）；Department of Medicinal Chemistry（药理化学系）；Cardiovascular Research Institute（心血管研究学院）；Department of Genetics and Molecular Biology（基因与分子生物学系）；Bioinformatics Research Center（生物信息学研究中心）
DrugReasoner: Interpretable Drug Approval Prediction with a Reasoning-augmented Language Model
Regenerative Medicine Research Center, Isfahan University of Medical Sciences（再生医学研究中心，伊斯法罕医科大学）；Isfahan University of Medical Sciences（伊斯法罕医科大学）；Isfahan Neuroscience Research Center, Isfahan University of Medical Sciences（伊斯法罕神经科学研究中心，伊斯法罕医科大学）；Department of Electrical and Computer Engineering, Isfahan University of Technology（电气与计算机工程系，伊斯法罕技术大学）
FusionDTI: Fine-grained Binding Discovery with Token-level Fusion for Drug-Target Interaction
School of Computing Science（计算科学学院）；School of Cancer Sciences（癌症科学学院）；Cancer Research UK Scotland Institute（英国癌症研究苏格兰研究所）；University of Glasgow（格拉斯哥大学）
Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations
Data Science Institute, School of Mathematics, Shandong University（数据科学研究院、数学学院、山东大学）；Academy of Mathematics and Systems Science, Chinese Academy of Sciences（数学与系统科学研究院、中国科学院）；Data Science Institute, Shandong University（数据科学研究院、山东大学）
