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.

To learn more, we welcome you to explore the topics on this page and join the orientation session on

June-August 2022

NAIPI - Click Here

LSU| LBRN - Click Here

Key Topics Covered:

Finding genomic data from epidemic outbreaks and research projects

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, association 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: viral genomes in host transcriptome Overview of NGS: reads, sequences, file formats Alignment, annotation and non-mapped reads Alignment to databases of viral genomes Associated Online Resources: RNA-seq and NGS sequencing Genomic Variation in NGS Data: Practical
	Multiple Sequence Alignment and Phylogeny Comparing sequences (Multiple Sequence Alignment) Finding a consensus sequence Identifying relationships between sequences (phylogeny, conservation) Associated Online Resource: Multiple Sequence Alignment - visualizing and filtering alignment
	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 Associated Online Resource: Comparing DNA sequences using Phylogenetic Analysis
	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 Associated Online Resource: Phylogenetic Analysis
	From Infection to Pandemic: viral adaptation Viral adaptation between Hosts Origins of Viral Adaptation Viral Transmission Cell entry and tissue tropism Associated Online Resource: DNA Structure & Variants
	Symptom severity: Disease progression and outcomes Symptoms Viral proteins Replication Immune evasion Associated Online Resource: Introduction to Genomics
	Hands-on project discussion EXAMPLE: the origin of human infection with MERS, SARS, and SARS-2 pandemics Associated Online Resource: COVID-19 Origin & Pathogenesis of SARS-COV2
	Rate of Mutation - mutation variant types Point mutations, substitutions, insertions Mutation types (synonymous/nonsynonymous; sense/missense) Mutation rate and fitness (frequency, entropy, conservation) Associated Online Resource: Mutability Analysis & Interpretation
	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 Associated Online Resources: Differential Mutation Analysis Copy Number Variation Analysis
	Host-pathogen interaction Protein-protein interaction and host response Immune response (adaptive, innate) Vaccine design: factors for consideration Associated Online Resource: COVID-19 Origin & Pathogenesis of SARS-COV2