Network pharmacology / / edited by Shao Li

• Pubblicazione: Singapore : , : Springer, , [2021]; ©2021
• Descrizione fisica: 1 online resource (480 pages)
• Disciplina: 769.563
• Soggetto topico: Pharmacy; Bioinformatics; Farmacologia; Bioinformàtica
• Soggetto genere / forma: Llibres electrònics
• Persona (resp. second.): LiShao
• Nota di contenuto: Intro -- Foreword -- Foreword -- Foreword -- Preface -- Contents -- Chapter 1: ``Network Target´´ Theory and Network Pharmacology -- 1.1 Network Pharmacology: Next Generation Medicine Research Mode -- 1.2 Key Role of TCM in the Origin and Development of Network Pharmacology -- 1.2.1 Original Method of Network Target Analysis -- 1.2.2 Common Methods of Network Target Analysis -- 1.3 Core Theory of Network Pharmacology: Network Target -- 1.3.1 Proposal and Development of Network Target Theory -- 1.3.2 The Concept of Network Target -- 1.4 Overview of Network Pharmacology Research Methods and Characteristics -- 1.4.1 Characteristics of ``Single Target-Partial Confrontation´´ Research Mode -- 1.4.2 Characteristics of ``Network Target-System Regulation´´ Research Mode -- 1.4.3 Typical Scenarios of Network Pharmacology Analysis -- 1.4.4 Characteristics, Advantages, Challenges, and Developmental Direction of Network Pharmacology Research -- References -- Chapter 2: Application of Network Pharmacology Based on Artificial Intelligence Algorithms in Drug Development -- 2.1 Introduction to Artificial Intelligence Methods in Network Pharmacology -- 2.1.1 Introduction to Artificial Intelligence Algorithms -- 2.1.2 Performance Evaluation Method for Artificial Intelligence Algorithms -- 2.1.3 Applications of Artificial Intelligence -- 2.1.4 Frontiers and Prospects of Artificial Intelligence -- 2.2 Application of Artificial Intelligence in Network Pharmacology Research -- 2.2.1 Prediction and Discovery of Drug Targets -- 2.2.2 Study on the Drug Property Mechanism -- 2.2.3 Discovery of New Drug Uses -- 2.2.4 Traditional Chinese Medicine and Its Therapeutic Theory -- 2.3 Application of Artificial Intelligence -- References -- Chapter 3: Common Network Pharmacology Databases -- 3.1 TCM Databases Commonly Used in Network Pharmacology. ; 3.1.1 ETCM: Encyclopedia of Traditional Chinese Medicine -- 3.1.1.1 Data Structure -- 3.1.1.2 Function Introduction -- 3.1.1.3 Characteristics -- 3.1.2 SymMap: Integrated TCM Database Focusing on the Association of Syndromes -- 3.1.2.1 Data Structure -- 3.1.2.2 Function Introduction -- 3.1.2.3 Characteristics -- 3.1.3 BATMAN-TCM: Bioinformatics Analysis Platform for the Molecular Mechanism of Traditional Chinese Medicine -- 3.1.3.1 Data Structure -- 3.1.3.2 Function Introduction -- 3.1.3.3 Characteristics -- 3.1.4 TCMID: TCM Integrated Database for Molecular Mechanism Analysis of TCM -- 3.1.4.1 Data Structure -- 3.1.4.2 Function Introduction -- 3.1.4.3 Characteristics -- 3.1.5 Other TCM Databases -- 3.2 Biological Databases Commonly Used in Network Pharmacology -- 3.2.1 Online Mendelian Inheritance in Man-OMIM -- 3.2.1.1 Database Content and Its Application in Network Pharmacology Research -- 3.2.1.2 Data Structure -- 3.2.1.3 Function Introduction -- 3.2.1.4 Characteristics -- 3.2.2 Human Phenotypic Ontology Database-HPO -- 3.2.2.1 Database Content and Its Application in Network Pharmacology Research -- 3.2.2.2 Data Structure -- 3.2.2.3 Function Introduction -- 3.2.2.4 Characteristics and Deficiencies -- 3.2.3 Disease Gene Association Database-DisGeNET -- 3.2.3.1 Data Structure -- 3.2.3.2 Function Introduction -- 3.2.3.3 Characteristics -- 3.2.4 Disease Information Data-MalaCards -- 3.2.4.1 Introduction and Usage of the Database -- 3.2.4.2 Characteristics -- 3.3 Related Databases of Commonly Used Gene Targets in Network Pharmacology -- 3.3.1 Therapeutic Target Database-TTD -- 3.3.1.1 Data Structure -- 3.3.1.2 Function Introduction -- 3.3.1.3 Characteristics -- 3.3.2 Protein Data Bank-PDB -- 3.3.2.1 Data Structure -- 3.3.2.2 Function Introduction -- 3.3.2.3 Characteristics and Deficiencies -- 3.3.3 Gene Information Database-GeneCards. ; 3.3.3.1 Data Structure -- 3.3.3.2 Applications/Functions in the Field of Molecular Biology -- 3.3.3.3 Characteristics and Deficiencies -- 3.3.4 Kyoto Encyclopedia of Genes and Genomes-KEGG -- 3.3.4.1 Data Structure -- 3.3.4.2 Function Introduction -- 3.3.4.3 Characteristics and Deficiencies -- 3.4 Protein Interaction Databases Commonly Used in Network Pharmacology -- 3.4.1 Biological Universal Interaction Database-BioGRID -- 3.4.1.1 Data Structure -- 3.4.1.2 Function Introduction -- 3.4.1.3 Characteristics -- 3.4.2 Database of Interacting Proteins-DIP -- 3.4.2.1 Data Structure -- 3.4.2.2 Function Introduction -- 3.4.2.3 Characteristics -- 3.4.3 Molecular Interaction Database-IntAct -- 3.4.3.1 Data Structure -- 3.4.3.2 Function Introduction -- 3.4.4 Database of Gene/Protein Interactions-STRING -- 3.4.4.1 Data Structure -- 3.4.4.2 Function Introduction -- 3.4.4.3 Characteristics -- References -- Chapter 4: Common Network Pharmacology Software -- 4.1 Software Functional Framework and Classification of Network Pharmacology -- 4.1.1 Overall Software Functional Requirements -- 4.1.2 Software Functional Framework and Classification of Network Pharmacology -- 4.2 Online Software Commonly Used in Network Pharmacology -- 4.2.1 Online Software for Drug-Target Prediction -- 4.2.2 Online Software for Drug Indication Analysis -- 4.2.3 Online Software for Gene Function Enrichment Analysis -- 4.2.4 Online Software for Constructing Protein Interaction Network -- 4.3 Software Based on Graphical Interface Operation -- 4.3.1 Differential Gene Enrichment Analysis Software -- 4.3.1.1 Software Installation -- 4.3.1.2 Data Preparation and Import -- 4.3.1.3 Setting Parameters and Running the Software -- 4.3.1.4 View Results -- 4.3.2 Network Analysis Software -- 4.3.2.1 Cytoscape -- Basic Use -- Exemplary Functional Components -- 4.3.2.2 Gephi Visualization Software. ; 4.3.2.3 Pajek Complex Network Visualization Software -- 4.4 Toolkit Based on Programming Languages -- 4.4.1 NetworkX -- 4.4.2 igraph -- References -- Chapter 5: Case Study of Network Pharmacology and Modernization of Traditional Chinese Medicine -- 5.1 Guide to this Chapter -- 5.2 Study of Network Pharmacology and TCM syndromes -- 5.2.1 Case Analysis of Network Pharmacology Research on Cold and Hot Syndromes and Corresponding Prescriptions -- 5.2.1.1 Research Objective -- 5.2.1.2 Data Source -- 5.2.1.3 Network Construction and Visualization -- 5.2.1.4 Analysis Index and Algorithm -- 5.2.1.5 Experimental Verification -- 5.2.1.6 Conclusion -- 5.2.2 Case Study and Analysis of ``Same Disease with Varying Syndromes´´ in Hepatic Fibrosis Caused by Chronic Hepatitis B -- 5.2.2.1 Research Objective -- 5.2.2.2 Data Source -- 5.2.2.3 Network Construction and Visualization -- 5.2.2.4 Analysis Index and Algorithm -- Network Analysis -- Analysis of Clinical Experimental Data -- 5.2.2.5 Main Conclusion -- 5.3 Case Study of Network Pharmacology and TCM Prescriptions -- 5.3.1 Research and Analysis of DMIM: An Interactive Information Model Based on the Spacing of TCM Compound Prescriptions -- 5.3.1.1 Research Objective -- 5.3.1.2 Data Source -- DMIM Analysis-Related Data -- Related LWDH Data -- 5.3.1.3 Network Construction and Visualization -- 5.3.1.4 Analysis Index and Algorithm -- 1) Mathematical Expression of TCM Prescriptions -- Mutual Information Entropy -- Spacing of Chinese Medicine Between Prescriptions -- DMIM Scoring System -- 5.3.1.5 Experimental Verification -- The Angiogenesis Activity of Chinese Medicines Screened by DMIM System was Evaluated Through In Vitro Experiments -- Experiment of Traditional Chinese Drug Pairs Predicted by DMIM -- 5.3.1.6 Main Conclusion -- 5.3.2 Network Pharmacology Analysis of Liuwei Dihuang Prescription. ; 5.3.2.1 Research Objective -- 5.3.2.2 Data Source -- 5.3.2.3 Network Construction and Visualization -- 5.3.2.4 Experimental Verification -- 5.3.2.5 Main Conclusion -- 5.4 Research Case on Network Pharmacology and TCM Formulation -- 5.4.1 Multi-component Synergy Recognition Method Based on Network Target -- 5.4.1.1 Research Objective -- 5.4.1.2 Data Source -- 5.4.1.3 Network Construction and Visualization -- 5.4.1.4 Analysis Index and Algorithm -- 5.4.1.5 Experimental Verification -- 5.4.1.6 Main Conclusion -- 5.4.2 Study on the Multi-target Mechanism of Artemisinin Against Plasmodium Falciparum -- 5.4.2.1 Research Objective -- 5.4.2.2 Data Source -- 5.4.2.3 Network Construction and Visualization -- 5.4.2.4 Analysis Index and Algorithm -- 5.4.2.5 Experimental Verification -- 5.4.2.6 Main Conclusion -- 5.5 Network Pharmacology and Ethnic Medicine Research Cases -- 5.5.1 Comparative Study and Analysis on Chemical Components and Pharmacological Effects of Three Species of Siegesbeckia -- 5.5.1.1 Research Objective -- 5.5.1.2 Data Source -- 5.5.1.3 Network Construction and Visualization -- 5.5.1.4 Analysis Index and Algorithm -- Compound similarity algorithm -- Network Analysis -- 5.5.1.5 Experimental Verification -- 5.5.1.6 Main Conclusion -- 5.5.2 Study and Analysis on the Mechanism of Hedyotis Diffusa Willd against Non-small Cell Lung Cancer -- 5.5.2.1 Research Objective -- 5.5.2.2 Data Source -- 5.5.2.3 Network Construction and Visualization -- 5.5.2.4 Analysis Index and Algorithm -- 5.5.2.5 Experimental Verification -- Animal Experiments -- Cell Experiments -- 5.5.2.6 Main Conclusion -- 5.6 Network Pharmacology and International Traditional Medicine Research Cases -- 5.6.1 Study and Analysis on Anti-cancer Activity of Calophyllum Brasiliense -- 5.6.1.1 Research Objective -- 5.6.1.2 Data Source -- 5.6.1.3 Network Construction and Visualization. ; 5.6.1.4 Analysis Index and Algorithm.
• Titolo autorizzato: Network Pharmacology
• ISBN: 981-16-0753-2
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910502975503321
• Lo trovi qui: Univ. Federico II