Bioinformatics for Infectious Diseases

This program is dedicated to the study of viral diversity and its role in epidemic infectious diseases that keep re-emerging, including zoonotic spillover, transmission between humans, and the process of viral and bacterial disease development. Participants will get a chance to learn about bioinformatics and analyze genomic data by applying various analysis approaches to study viral genomes.

As a result, you will learn to understand relationships between viral strains and haplotypes, find differences in sequence data, and see the implications for drug and vaccine design. This program will provide opportunities to practice analyzing data to gain hands-on experience with curated datasets from public domain collections, guided by experts with bioinformatics experience and knowledge about virology. 

Key Topics Covered:

  Finding genomic data from epidemic outbreaks and research projects (i.e. genomic sequences and NGS data)

Many types of omics data require step-by-step preparation, exploration, annotation, and visualization to understand. The T-BioInfo platform was designed for big multi-omics data analysis hiding the complexities of data with a user-friendly and intuitive interface that eliminates the need for coding and advanced machine learning algorithms for data integration and mining.

Phylogenetics and Multiple Sequence Alignment (MSA)

A program that embeds data-driven concepts into biological projects, spanning the student learning journey from observer to participant in research. Project-based learning for big data bioinformatics is to go beyond the theory with real datasets, projects, and expert mentors. Work with curated datasets from publicly available repositories with easy-to-follow tutorials.

Downstream analysis of genomic data (differential mutations, data mining, and association with phenotype)

Data processing for Next Generation Sequencing, Mass-Spectroscopy, Structural and phenotypic data. Build and adapt pipelines using similar approaches to data mapping, quantification, and annotation that are used to prepare data for downstream statistical analysis, train machine learning models and annotate features.

GWAS studies for viral and bacterial genomes & Variation mapping on protein structures

Online bioinformatics coding exercises to learn and explore R and Python scripting and understand how to analyze and visualize -omics data to extract meaningful insights from large biological datasets. Learn, practice, and achieve bioinformatics greatness with concise exercises and interesting challenges right in the comfort of your browser!

Program Syllabus : Bioinformatics for Infectious Diseases

SESSIONS TOPICS

DESCRIPTION

Next Generation Sequencing

Next-generation sequencing: viral genomes in host transcriptome 

  • Overview of NGS: reads, sequences, file formats  
  • Alignment, annotation and non-mapped reads  
  • Alignment to databases of viral genomes   


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Multiple Sequence Alignment

Multiple Sequence Alignment and Phylogeny

  • Comparing sequences (Multiple Sequence Alignment)
  • Finding a consensus sequence
  • Identifying relationships between sequences (phylogeny, conservation)

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Hands-On session: Bioinformatics for Infectious Diseases

Hands-on session, preparing and running your pipeline

  • Multiple sequence alignment of viral genomes and building a phylogenetic tree
  • Finding full genome sequences and preparing FASTA files
  • Selecting appropriate genomic sequences
  • Preparing a full pipeline of MSA and Phylogeny

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Q&A: Discussion of pipeline results

Q&A and DISCUSSION of pipeline results

  • Workflows: what to do if we have FASTA/FASTQ files?
  • Which databases to use: Detection of viral genomes by mapping on databases
  • Interpretation of Phylogenetic Analysis: Evolutionary relationships between genomes, evolutionary time

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Bioinformatics for Infectious Diseases: From infection to pandemic

From Infection to Pandemic: viral adaptation 

  • Viral adaptation between Hosts
  • Origins of Viral Adaptation
  • Viral Transmission
  • Cell entry and tissue tropism

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Bioinformatics for Infectious Diseases: Disease progression and outcomes

Symptom severity: Disease progression and outcomes

  • Symptoms
  • Viral proteins
  • Replication
  • Immune evasion

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The origin of human infection with MERS, SARS and SARS-2 pandemic

Hands-on project discussion

  • EXAMPLE: the origin of human infection with MERS, SARS, and SARS-2 pandemics

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Rate of mutation- mutation variant types

Rate of Mutation - mutation variant types

  • Point mutations, substitutions, insertions
  • Mutation types (synonymous/nonsynonymous; sense/missense)
  • Mutation rate and fitness (frequency, entropy, conservation)
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Mutation Annotation and significance

Mutation Annotation & Significance for analysis

  • Analysis of mutation variants and annotation of codon/amino-acid and chemical properties
  • Location on genome and protein function relationship to mutation accumulation
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Host pathogen interaction

Host-pathogen interaction

  • Protein-protein interaction and host response
  • Immune response (adaptive, innate)
  • Vaccine design: factors for consideration
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