In silico Vaccine Design from NGS data and whole genome

Price 9999 | USD $297

Live class will start from 8 Oct 2021.

Attend 2 demo sessions free and pay only after you are satisfied.

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About Course

The advent of next generation sequencing has remapped in silico vaccine design with availability of variant dataset for the pathogens in the form of NGS data. It necessitated in silico vaccine design – the reverse vaccine techniques to start from raw reads to pan genome construction and epitope detection. The course will address multi-epitope vaccine design in silico starting from NGS raw reads. The course will touch upon variant calling and genome assembly of the pathogens to evaluate final epitopes such that the designed multi-epitope doesn’t get affected with evolution of new viral strains. The course will use SARS-CoV2 NGS reads and genome sequences available in the open source platform as examples dataset. To ensure Biologist to learn the same efficiently, the course will introduce Linux OS, Python basics required for the vaccine design protocol.

Course highlights


  1. Immune informatics and the concept of Reverse Vaccinology
  2. From genome to multi-epitope vaccine design
  3. File handling and manipulation in Linux
  4. Practical: Genome sequence resources – Databases, Sequence retrieval, reading and comparison using linux commands
  5. Understanding genome/gene/protein sequence formats: FASTA, FASTQ
  6. Installation comparative genomic analysis software: BLAST
  7. User registration in Galaxy server
  8. Project: Retrieve 10 most closely related genome sequences of SARS-CoV-2 (NC_045512.2).
  1. Reference based genome assembly from NGS based Raw reads.
  2. Python programming for vaccine design – Regular Expressions and string comparison
  3. Practical: QC, alignment and variant calling from NGS reads - FastQC, Trimmomatic, MultiQC, Burrow wheeler aligner, Genome Analysis Tool Kit, snpEff, snpSIFT and deeptools
  4. Practical: Constructing Reference based draft genome
  5. Project: Construct reference based draft genome for 10 given NGS datasets. The assignment need to done using Galaxy web server and standalone software.
  1. De novo genome assembly, annotation, draft genome construction.
  2. Multiple sequence alignment and extracting cold spot regions in the consensus genome.
  3. Practical: De novo genome assembly, annotation
  4. Practical: Consensus genome construction and genome annotation - prokka
  5. Practical: Visualization of cold spot region in IGV, Artemis
  6. Project: Construct draft genome through de novo genome assembly for the given NGS dataset.
  1. Epitope prediction tools and algorithms
  2. B-cell epitope prediction
  3. B-cell epitope databases
  4. Practical: ABCpred, EMBOSS, VaxiJen
  5. Practical: Screening peptides predicted as epitope in all tools using python
  6. Project: Predict epitopes using ABCpred and VaxiJen and report common epitopes observed in both the tools.
  1. T-cell epitope databases and tools: Helper T cell and Cytotoxic T cell epitopes
  2. FRED2 - An Immunoinformatics Framework for Python
  3. Practical: Helper T cell epitope prediction
  4. Practical: Cytotoxic T cell epitope prediction
  5. Practical: Conservancy, Coverage and HLApred analysis
  6. Practical: T-cell epitope prediction using FRED2
  7. Practical: Using Python scripting to filter T-cell epitopes
  8. Practical: Project: Identify peptides have propensity to acts as Helper as well as CTL T-cell epitopes using PREDIVAC, NetMHCpan 3.1, NetMHC 4.0, NetCTL and IEDB recommended method. Report top 10 T-cell epitopes.
  1. Multi-epitope vaccine design concept and success stories
  2. Structure level evaluation of multi epitope vaccine and roads ahead
  3. Practical: Multi-epitope vaccine design, in silico characterization, structure prediction and evaluation.
  4. Practical: Discontinuous vaccine prediction.
  5. Practical: Protein-peptide docking with host proteins.
  6. Practical: In silico vaccine expression
  7. Project: Design multi-epitope vaccine with a selected set of epitopes of your choice and perform in silico characterization.

Features available in our live classes

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Certificate of completion

Life time study material access

Doubt solving at any time

Job opportunities


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Our values lie in our instructors

Anand Kumar
Python for Bioinformatics, Vaccine designing

Anand is the Co-Founder and CTO of ReadMyCourse. He has 5 years of experience in working with computation biology, Machine Learning, and Vaccine designing. He has co-authored various research papers in reputed journals and has advanced the career of thousands of students.

Dr. Dibyabhaba Pradhan
NGS data analysis, Vaccine designing, Bioanalyst

Dr. Dibyabhaba Pradhan is a Post-doctoral Research Scientist. He is a PhD in Bioinformatics and has more than 12 years of Research and teaching experience in High throughput NGS data analysis, Computer-aided vaccine design, Rational Drug Design and Medical Informatics. He co-authored more than 53 research papers in International and National Journals of repute.

Nirupma Singh
Python, R, Data Analysis, Machine Learning

Nirupma has 5 years of experience with R and Python programming languages for handling and analysing biological data and implement machine learning. She has a post-graduate in Microbiology therefore, She can understand and interpret the biological data quite well and could provide valuable insights. She enjoys interactive teaching with the learners and give her best to it.

Sharon Priya Alexander
Drug designing, Bioinformatics tools

Sharon Priya Alexander has Masters Degree in Bioinformatics bagged late Dr. P. Subramanyam IAS Gold Medal for being a University topper. He has co-authored various research papers in reputed journals. Currently Pursuing PhD in drug designing.


If you miss the class you can attent in any other session. You can view recorded sessions also.

Yes you can attend demo session for free. Before the final class will be started you can attend demo live classes.

Yes you are eligible for refund in the period of three classes.

You will get the certificate after completion of all the live sessions and study materials.

In silico Vaccine Design from NGS data and whole genome