Course Content
Computational Vaccine Design | Book-Club |
Book
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Computational Vaccine Design
chapter 1
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Abstract
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1. Introduction
06:37 -
2. Basic Immunology Principles
07:47 -
3. What Is a Vaccine and How Vaccines Work
06:41 -
4 . Rational Vaccine Design and Vaccine Platforms
07:43 -
5. Concluding Remarks
07:43
Chapter 2
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1 Introduction
05:50 -
2 2 1 Materials Equipment Software
06:22 -
3 1 Methods Kinetics
06:54 -
3 2 Epitope Binning of mAbs
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3 3 Epitope Binning of Serum pAbs
06:06 -
4 Notes
05:46
Chapter 3
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Abstract
05:48 -
1 Introduction
06:28 -
2 1 Materials
05:31 -
2 2 ClusTCR Tool
07:21 -
2 3 2 4 TCRex Tool
05:46 -
2 4 TCRex Tool Code Repository and Tutorials
04:14 -
3 Methods 3 1 Clustering Repertoires with ClusTCR
06:24 -
3 2 Clustering and Annotation of T Cell Receptor Repertoires
06:28 -
4 Notes
04:26
Chapter 4
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ABSTRACT
07:14 -
1 Introduction
06:03 -
2 Workflow
05:12 -
3 3 1 The Protocol Data
07:06 -
3 2 Cell Type Labeling and Supervised Machine Learning
05:31 -
3 3 Prediction of Cell Types by Supervised Machine Learning
05:33 -
3 4 Discussion
04:37 -
4 NOTE
05:26
Chapter 5
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Abstract
06:45 -
1 Introduction
07:59 -
2 Materials
06:00 -
3 1 Methods Thaw Cryopreserved PBMC
05:09 -
3 2 Plate PBMC Sterile Conditions
06:26 -
4 Notes
07:11
Chapter 6
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Abstract
07:53 -
1 Introduction
06:32 -
2 1 Materials
07:21 -
3 3 1 Methods Antigen
06:57 -
3 2 Reconstituted In Vitro Antigen
06:46 -
3 3 Prioritizing Candidate Epitopes
06:04 -
3 4 Evaluating CD4+ T Cell Reactivity
07:10 -
4 Notes
07:46
Chapter7
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Abstract
06:11 -
1 Introduction
00:00 -
2 2 1 Materials Software
05:22 -
3 3 1 Methods
05:52 -
4 Notes
04:50
Chapter 8
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Abstract
05:01 -
1 Introduction
06:48 -
2 2 1 Materials
05:56 -
3 3 1 Methods Mesoporous Silicon Production
06:23 -
4 Notes
05:51
Chapter 9
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Abst
07:20 -
1 Introduction
05:28 -
2 2 1 IEDB Data Curation
06:50 -
3 Querying the IEDB Data
05:40 -
4 Navigating the Results of IEDB Queries
05:42 -
5 IEDB Community Outreach
04:23 -
6 Adapting IEDB Processes to CEDAR
04:50 -
7 Searching the CEDAR Database
05:58 -
8 Two Sibling Resources
00:00 -
9 IEDB and CEDAR Two Sibling Databases to Serve the Global Scientific Community 9
05:52
Chapter 10
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Abstract
06:18 -
2 2 1 Materials and Methods WHOIUIS Allergen Sub Committee Database
05:28 -
2 2 AllFam—The Database of Allergen Family
05:33 -
2 3 Databases of Allergens and their Epitopes
05:24 -
2 4 AllergenOnline Database
05:35 -
2 5 2 5 1 AllerBase Description of AllerBase
06:17 -
3 Notes
04:43
Chapter 11
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Abstract
06:04 -
1 Introduction
06:11 -
2 Materials
04:56 -
3 3 1 Methods
07:01 -
4 Notes
05:26
Chapter 12
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Abstract
07:51 -
1 Introduction
06:27 -
2 2 1 Materials The EPIPOX Resource
05:59 -
2 2 Description of Web Interface
05:19 -
3 3 1 Methods
06:13 -
3 4 Getting Search Results
05:32 -
4 Notes
04:48
Chapter 13
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Abstract
07:26 -
1 Introduction
05:41 -
2 Materials
04:43 -
3 Methods
08:14 -
4 Notes
07:07
Chapter 14
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Abstract
05:25 -
1 Introduction
05:30 -
2 Materials
05:32 -
3 1 Methods
06:30 -
4 Notes
06:13
Chapter 15
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Abstract
06:11 -
1 Introduction
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1 1 C Terminal Antigen Processing as a Predictor of T Cell Epitope
00:00 -
1 2 NetCleave Advantages
06:53 -
1 3 Program
06:25 -
2 2 1 Using the NetCleave Algorithm
08:21 -
2 2 2 2 1 Model Retraining Retraining
06:36 -
3 Notes
06:49
Chapter 16
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Abstract
07:01 -
1 1 1 Introduction
05:13 -
1 2 TAP Transport of Peptides
05:43 -
1 3 Predicting Peptide Binding to TAP
05:38 -
2 2 1 Materials Sequence Collection
05:36 -
2 2 TAPREG Tool
06:13 -
3 3 1 Methods Predicting TAP Binding Affinity Using Peptides as Input
06:35 -
3 2 Predicting TAP Binding Affinity Using as Input a Protein Sequence
05:18 -
4 Notes
06:09
Chapter 17
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Abstract
06:11 -
1 Introduction
06:15 -
2 2 1 Materials Structures Software
06:15 -
3 3 1 Methods
04:53 -
3 2 Pre docking Data Preparation
06:09 -
3 3 Molecular Docking
06:57 -
3 4 Construction of the Docking Based Quantitative Matrix QM
06:17 -
4 Notes
04:47
Chapter 18
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Abstract
06:36 -
1 Introduction
07:43 -
2 2 1 Useful Information Code Block Colors
05:08 -
3 3 1 PANDORA Protocols Installation
04:24 -
3 2 Download the Template Database or Build the Database
05:10 -
3 3 Protocol 1— Model a PeptideMHC I Complex, a Simple
04:37 -
3 4 Protocol 2— Model a PeptideMHC I Complex, a Comprehensive Python Scenario
05:37 -
3 5 Protocol 3— Model a PeptideMHC II Complex
05:37 -
3 6 Protocol 4—Run PANDORA Wrapper on Multiple Cases
05:41 -
3 7 Model Quality Evaluations
05:02 -
3 8 Anticipated
02:56 -
4 Limitations of PANDORA
05:34 -
5 Notes
07:11
Chapter 19
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Abstract
00:00 -
1 Introduction
08:11 -
2 Software
05:19 -
3 Methods
05:22 -
3 1 Model Building for Peptides
06:48 -
3 3 Model Building for TCR CDR3 Loops
05:48 -
4 Notes
05:54
Chapter 20
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Abstract
05:47 -
2 2 1 Materials
05:46 -
2 2 2 2 1 Sequences Dataset of Immunogenic Proteins
07:07 -
3 1 Methods Splitting the Datasets
06:37 -
3 2 Transformation of the Protein Sequences into Numerical Vectors
04:25 -
3 3 Auto and Cross Covariance Transformation
07:07 -
3 4 Data Preparation
05:12 -
3 5 Training a Classification Model
05:08 -
3 6 Assessment of the Model Performance
05:31 -
3 8 Machine Learning Methods
06:58 -
3 9 ML Model Assessment
05:56 -
4 Notes
04:09
Chapter 21
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Abstract
06:25 -
1 Introduction
06:23 -
2 2 1 Materials Sequences
05:01 -
3 3 1 Methods Construction of a Deep Learning Model
07:34 -
3 2 Testing the Models
06:57 -
4 Notes
06:55
Chapter 22
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Abstract
06:59 -
1 Introduction
00:00 -
2 Materials
06:59 -
3 3 1 Methods Brief Description of IL6pred
05:32 -
3 2 Identification of IL6 Inducing Peptide
05:20 -
3 3 Designing of Non IL6 Inducing Peptides
05:44 -
3 4 Identification of IL6 Inducing Peptides in Antigen
04:38 -
3 5 Scanning of IL6 Specific Motifs
05:44 -
3 6 BLAST Based Similarity Search
05:29 -
3 7 Standalone Package
05:11 -
4 Notes
05:48
Chapter 23
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Abstract
07:00 -
1 Introduction
00:00 -
2 Materials
05:53 -
3 1 Methods Description of IL13pred Tool
05:35 -
3 2 Prediction of IL13 Inducing Peptides
05:45 -
3 3 Predicting IL13 Inducer Peptides
05:17 -
3 4 Scanning of IL13 Inducing Regions
05:06 -
3 5 Similarity Search Based on BLAST
05:09 -
3 6 Standalone Version of IL13pred
05:02 -
4 Notes
06:19
Chapter 24
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Abstract
07:18 -
1 Introduction
06:23 -
2 Materials
04:55 -
3 3 1 Methods Obtain Core Proteome of the Target Bacterium
05:55 -
3 2 Prediction of Protein Subcellular Localization
07:17 -
3 3 Estimation of Protein Expression Abundance
06:31 -
3 4 Prediction of T and B Cell Linear Epitopes
05:34 -
4 Notes
06:36
Chapter 25
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Abstract
07:14 -
1 Introduction
06:05 -
2 2 1 Materials Computational Workstation
05:39 -
3 3 1 Methods Sequence Retrieval
06:14 -
3 12 Determination of Physiochemical Properties
06:27 -
3 16 Molecular Dynamics Simulations
07:21 -
4 Notes
05:46
Chapter 26
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Abstract
05:45 -
1 Introduction
06:18 -
1 1 Rational Structure Based Vaccine Design
05:33 -
2 2 1 Materials Software and Servers
06:20 -
3 3 1 Methods for COVID 19 Vaccine Design and Simulation Structural
07:22 -
..
07:12 -
3 3 In Silico Vaccine Design
05:39 -
3 4 MD Simulation of Docked SARS CoV 2 SpikeACE2 Protein Complexes
07:00 -
3 5 Calculation of Binding Free Energies of Spike ACE2 Complexes
05:26 -
3 6 Molecular Dynamics Simulation
07:09 -
3 7 Spike Protein Vaccine Design and Generation
06:38 -
3 8 In Vivo Immunogenicity Testing
06:26 -
3 9 Immunogenicity Assessment by Spike Protein Binding
07:41 -
3 10 Assessment of SARS CoV 2 Neutralizing Antibody Using Lentivirus Pseudotype Assay
05:59 -
4 Notes
05:49
Chapter 27
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Abstract
05:16 -
1 1 Reverse Vaccinology Approach
06:16 -
2 2 Materials
04:11 -
3 3 1 Methods
06:09 -
3 2 Collection of Identification of New Vaccine Candidates for Influenza A Virus
08:44 -
4 Notes
05:01
Chapter 28
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Abstract
08:02 -
1 Introduction
06:26 -
2 2 1 Methods
05:37 -
2 2 CD8 Epitope Selection 2 2 1 Binding IEDB MHC I control
06:13 -
2 3 CD4 Epitope Selection
05:45 -
2 4 IFN γ Inducing Epitopes on IFNepitope Server
06:39 -
2 6 IEDB Population Coverage
05:14 -
2 8 Vaccine Structure Design
06:36 -
2 9 1 Linkers Vaccine Safety
05:54 -
2 10 Vaccine Antigenicity
06:52 -
2 14 B Cell Epitope
05:33 -
3 Notes
05:58
Chapter 29
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Abstract
06:03 -
1 Introduction
06:12 -
2 Materials
03:50 -
2 1 Software, Servers, and Databases
06:47 -
3 3 1 Methods
06:06 -
3 3 Construction of the Vaccine Architecture and Physicochemical Characterization
07:20 -
3 4 Determination of Vaccine Efficacy in Triggering Innate and Adaptive Immunity
06:08 -
3 5 Determination of Stability of Binding of Vaccine to the Target Proteins
08:58 -
3 6 Immune Simulation with the Vaccine
06:40 -
3 7 Cloning of the Vaccine Construct
05:52 -
4 Notes
07:09
Chapter 30
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Abstract
06:26 -
241—
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1 Introduction
07:04 -
2 Materials
05:33 -
3 3 1 Methods
03:52 -
3 2 Multiple Sequence Alignment and Identification of Conserved Regions
05:10 -
3 3 Linear B Cell Epitope Analysis
06:28 -
3 4 Prediction of MHC Class I Epitopes 3 5
05:39 -
3 5 MHC
06:13 -
3 6 Population Coverage Analysis
05:24 -
4 Notes
07:11
Chapter 31
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Abstract
06:55 -
1 Introduction
05:16 -
2 Materials
05:16 -
3 3 1 Methods Proteome
05:57 -
3 2 Prediction of CTL, HTL, and B Cell Epitopes
06:54 -
3 3 Construction of Multi Epitopes Subunit Vaccine
06:31 -
3 4 Physicochemical Properties Analysis and 3D Structure Modeling
06:10 -
3 5 Molecular Docking with Human TLRs
07:48 -
4 Notes
06:21
Chapter 32
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Abstract
05:58 -
1 Introduction
05:55 -
2 2 1 2 2 Materials Sequences Protein Structures
05:35 -
3 3 1 Methods Sequence Processing
06:01 -
3 2 Clusterization and Filtering
06:42 -
3 3 Alignment and Conservation Analysis
00:00 -
3 4 CD8+ T Cell Epitope Prediction
07:01 -
3 5 CD4+ T Cell Epitope Prediction
08:17 -
3 6 B Cell Epitope Prediction
00:00 -
3 7 Homology Analysis
05:47 -
4 Notes
07:48
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