Computation in Bioinformatics
Multidisciplinary Applications
Herausgegeben:Balamurugan, S.; Krishnan, Anand T.; Goyal, Dinesh; Chandrasekaran, Balakumar
Computation in Bioinformatics
Multidisciplinary Applications
Herausgegeben:Balamurugan, S.; Krishnan, Anand T.; Goyal, Dinesh; Chandrasekaran, Balakumar
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Die Bioinformatik ist ein Feld zwischen der Biologie und der Informationstechnologie. Das Werk deckt zahlreiche Gebiete der Bioinformatik ab, beginnend mit den grundlegenden Prinzipien, Konzepten und multidisziplinären Anwendungsbereichen. Es enthält eine Reihe von Kapiteln, in denen die Rolle der Bioinformatik bei der Entwicklung und Entdeckung von Arzneimitteln beschrieben wird, insbesondere in Bezug auf die molekulare Modellierung. In anderen Kapiteln werden Themen wie in-silico-Design, Proteinmodellierung, DNA-Mikroarray-Analyse, DNA-RNA-Barcoding und Gensequenzierung ausführlich…mehr
- Biomedical Data Mining for Information Retrieval258,99 €
- Data Analytics in Bioinformatics252,99 €
- Emerging Technologies for Healthcare258,99 €
- Bioinformatics and Medical Applications258,99 €
- Computational Intelligence and Healthcare Informatics258,99 €
- Data Mining and Machine Learning Applications258,99 €
- Advanced Healthcare Systems258,99 €
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- Produktdetails
- Verlag: Wiley & Sons / Wiley-Scrivener
- Artikelnr. des Verlages: 1W119654710
- 1. Auflage
- Seitenzahl: 352
- Erscheinungstermin: 19. Oktober 2021
- Englisch
- Abmessung: 237mm x 163mm x 23mm
- Gewicht: 620g
- ISBN-13: 9781119654711
- ISBN-10: 1119654718
- Artikelnr.: 59545514
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Wiley & Sons / Wiley-Scrivener
- Artikelnr. des Verlages: 1W119654710
- 1. Auflage
- Seitenzahl: 352
- Erscheinungstermin: 19. Oktober 2021
- Englisch
- Abmessung: 237mm x 163mm x 23mm
- Gewicht: 620g
- ISBN-13: 9781119654711
- ISBN-10: 1119654718
- Artikelnr.: 59545514
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
1 Bioinfomatics as a Tool in Drug Designing 1
Rene Barbie Browne, Shiny C. Thomas and Jayanti Datta Roy
1.1 Introduction 1
1.2 Steps Involved in Drug Designing 3
1.2.1 Identification of the Target Protein/Enzyme 5
1.2.2 Detection of Molecular Site (Active Site) in the Target Protein 6
1.2.3 Molecular Modeling 6
1.2.4 Virtual Screening 9
1.2.5 Molecular Docking 10
1.2.6 QSAR (Quantitative Structure-Activity Relationship) 12
1.2.7 Pharmacophore Modeling 14
1.2.8 Solubility of Molecule 14
1.2.9 Molecular Dynamic Simulation 14
1.2.10 ADME Prediction 15
1.3 Various Softwares Used in the Steps of Drug Designing 16
1.4 Applications 18
1.5 Conclusion 20
References 20
2 New Strategies in Drug Discovery 25
Vivek Chavda, Yogita Thalkari and Swati Marwadi
2.1 Introduction 26
2.2 Road Toward Advancement 27
2.3 Methodology 30
2.3.1 Target Identification 30
2.3.2 Docking-Based Virtual Screening 32
2.3.3 Conformation Sampling 33
2.3.4 Scoring Function 34
2.3.5 Molecular Similarity Methods 35
2.3.6 Virtual Library Construction 37
2.3.7 Sequence-Based Drug Design 37
2.4 Role of OMICS Technology 38
2.5 High-Throughput Screening and Its Tools 40
2.6 Chemoinformatic 44
2.6.1 Exploratory Data Analysis 45
2.6.2 Example Discovery 46
2.6.3 Pattern Explanation 46
2.6.4 New Technologies 46
2.7 Concluding Remarks and Future Prospects 46
References 48
3 Role of Bioinformatics in Early Drug Discovery: An Overview and Perspective 49
Shasank S. Swain and Tahziba Hussain
3.1 Introduction 50
3.2 Bioinformatics and Drug Discovery 51
3.2.1 Structure-Based Drug Design (SBDD) 52
3.2.2 Ligand-Based Drug Design (LBDD) 53
3.3 Bioinformatics Tools in Early Drug Discovery 54
3.3.1 Possible Biological Activity Prediction Tools 55
3.3.2 Possible Physicochemical and Drug-Likeness Properties Verification Tools 58
3.3.3 Possible Toxicity and ADME/T Profile Prediction Tools 60
3.4 Future Directions With Bioinformatics Tool 61
3.5 Conclusion 63
Acknowledgements 64
References 64
4 Role of Data Mining in Bioinformatics 69
Vivek P. Chavda, Amit Sorathiya, Disha Valu and Swati Marwadi
4.1 Introduction 70
4.2 Data Mining Methods/Techniques 71
4.2.1 Classification 71
4.2.1.1 Statistical Techniques 71
4.2.1.2 Clustering Technique 73
4.2.1.3 Visualization 74
4.2.1.4 Induction Decision Tree Technique 74
4.2.1.5 Neural Network 75
4.2.1.6 Association Rule Technique 75
4.2.1.7 Classification 75
4.3 DNA Data Analysis 77
4.4 RNA Data Analysis 79
4.5 Protein Data Analysis 79
4.6 Biomedical Data Analysis 80
4.7 Conclusion and Future Prospects 81
References 81
5 In Silico Protein Design and Virtual Screening 85
Vivek P. Chavda, Zeel Patel, Yashti Parmar and Disha Chavda
5.1 Introduction 86
5.2 Virtual Screening Process 88
5.2.1 Before Virtual Screening 90
5.2.2 General Process of Virtual Screening 90
5.2.2.1 Step 1 (The Establishment of the Receptor Model) 91
5.2.2.2 Step 2 (The Generation of Small-Molecule Libraries) 92
5.2.2.3 Step 3 (Molecular Docking) 92
5.2.2.4 Step 4 (Selection of Lead Prot
1 Bioinfomatics as a Tool in Drug Designing 1
Rene Barbie Browne, Shiny C. Thomas and Jayanti Datta Roy
1.1 Introduction 1
1.2 Steps Involved in Drug Designing 3
1.2.1 Identification of the Target Protein/Enzyme 5
1.2.2 Detection of Molecular Site (Active Site) in the Target Protein 6
1.2.3 Molecular Modeling 6
1.2.4 Virtual Screening 9
1.2.5 Molecular Docking 10
1.2.6 QSAR (Quantitative Structure-Activity Relationship) 12
1.2.7 Pharmacophore Modeling 14
1.2.8 Solubility of Molecule 14
1.2.9 Molecular Dynamic Simulation 14
1.2.10 ADME Prediction 15
1.3 Various Softwares Used in the Steps of Drug Designing 16
1.4 Applications 18
1.5 Conclusion 20
References 20
2 New Strategies in Drug Discovery 25
Vivek Chavda, Yogita Thalkari and Swati Marwadi
2.1 Introduction 26
2.2 Road Toward Advancement 27
2.3 Methodology 30
2.3.1 Target Identification 30
2.3.2 Docking-Based Virtual Screening 32
2.3.3 Conformation Sampling 33
2.3.4 Scoring Function 34
2.3.5 Molecular Similarity Methods 35
2.3.6 Virtual Library Construction 37
2.3.7 Sequence-Based Drug Design 37
2.4 Role of OMICS Technology 38
2.5 High-Throughput Screening and Its Tools 40
2.6 Chemoinformatic 44
2.6.1 Exploratory Data Analysis 45
2.6.2 Example Discovery 46
2.6.3 Pattern Explanation 46
2.6.4 New Technologies 46
2.7 Concluding Remarks and Future Prospects 46
References 48
3 Role of Bioinformatics in Early Drug Discovery: An Overview and Perspective 49
Shasank S. Swain and Tahziba Hussain
3.1 Introduction 50
3.2 Bioinformatics and Drug Discovery 51
3.2.1 Structure-Based Drug Design (SBDD) 52
3.2.2 Ligand-Based Drug Design (LBDD) 53
3.3 Bioinformatics Tools in Early Drug Discovery 54
3.3.1 Possible Biological Activity Prediction Tools 55
3.3.2 Possible Physicochemical and Drug-Likeness Properties Verification Tools 58
3.3.3 Possible Toxicity and ADME/T Profile Prediction Tools 60
3.4 Future Directions With Bioinformatics Tool 61
3.5 Conclusion 63
Acknowledgements 64
References 64
4 Role of Data Mining in Bioinformatics 69
Vivek P. Chavda, Amit Sorathiya, Disha Valu and Swati Marwadi
4.1 Introduction 70
4.2 Data Mining Methods/Techniques 71
4.2.1 Classification 71
4.2.1.1 Statistical Techniques 71
4.2.1.2 Clustering Technique 73
4.2.1.3 Visualization 74
4.2.1.4 Induction Decision Tree Technique 74
4.2.1.5 Neural Network 75
4.2.1.6 Association Rule Technique 75
4.2.1.7 Classification 75
4.3 DNA Data Analysis 77
4.4 RNA Data Analysis 79
4.5 Protein Data Analysis 79
4.6 Biomedical Data Analysis 80
4.7 Conclusion and Future Prospects 81
References 81
5 In Silico Protein Design and Virtual Screening 85
Vivek P. Chavda, Zeel Patel, Yashti Parmar and Disha Chavda
5.1 Introduction 86
5.2 Virtual Screening Process 88
5.2.1 Before Virtual Screening 90
5.2.2 General Process of Virtual Screening 90
5.2.2.1 Step 1 (The Establishment of the Receptor Model) 91
5.2.2.2 Step 2 (The Generation of Small-Molecule Libraries) 92
5.2.2.3 Step 3 (Molecular Docking) 92
5.2.2.4 Step 4 (Selection of Lead Prot