Courses for beginners with little or no prior knowledge in bioinformatics:

• Introduction to Bioinformatics: Overview of bioinformatics, genomics, proteomics, and computational biology.

• Basic Programming for Bioinformatics: Introduction to Linux, Shell, Python, R, or MATLAB for biological data analysis, with key topics on loops, functions, and libraries (e.g., Biopython, Tidyverse).

• Biostatistics for Beginners: Fundamental statistical concepts, including hypothesis testing, regression analysis, and data visualization.

• Introduction to Databases in Bioinformatics: Understanding and querying biological databases (NCBI, UniProt, Ensembl, RCSB) using SQL and web interfaces.

• Basic Molecular Bioinformatics: PCR primer design, Sanger sequence analysis, and NCBI BLAST.

• Introduction to Structure-Based Drug Discovery (SBDD)

• Molecular Modeling and Docking Techniques

• Protein-Ligand Interactions and Binding Site Analysis

• Computational Tools for SBDD (AutoDock, PyMOL, Chimera)

• Virtual Screening: Ligand-Based vs Structure-Based

• Pharmacophore Modeling and Drug-Likeness Evaluation

• ADMET Prediction in Drug Discovery

• Case Studies: Successful SBDD Applications

• AI and Machine Learning in Drug Discovery

• Hands-on: Docking and Virtual Screening

• Current Trends and Future Directions in SBDD

Module 1: Introduction to Bioinformatics

• What is Bioinformatics?

• History and Scope of Bioinformatics

• Biological Databases (NCBI, EMBL-EBI, UniProt)

• Sequence Formats (FASTA, GenBank)

• Basic Sequence Analysis Tools (BLAST, FASTA)

Module 2: Genome Assembly and Annotation

• Overview of Genome Sequencing Technologies (Sanger, NGS)

• Genome Assembly Algorithms (de novo, reference-guided)

• Assembly of long read, short read and hybrid.

• Annotation of Prokaryotic Genomes

• Gene Prediction and Functional Annotation

• Using Annotation Tools (Prokka, RAST)

Module 3: Data Visualization

• Circular Genome Maps (CGView)

• Comparative Genome Visualization (BRIG)

• Visualization of Gene Expression Data

• Interactive Data Exploration Tools

Module 4: Antimicrobial Resistance Genes

• Mechanisms of Antimicrobial Resistance

• Detection and Characterization of Resistance Genes

• Analysis of Resistance Gene Spread and Evolution

• Bioinformatics Tools for Resistance Gene Prediction (ResFinder, CARD)

Module 5: Plasmid Annotation and Analysis

• Plasmid Biology and Classification

• Plasmid Annotation and Visualization

• Analysis of Plasmid Replicons and Transfer Mechanisms

• Identification of Mobile Genetic Elements on Plasmids

Module 6: Mobile Genetic Elements

• Types of Mobile Genetic Elements (Transposons, Integrons, Bacteriophages)

• Mechanisms of Horizontal Gene Transfer

• Impact of Mobile Genetic Elements on Microbial Evolution

• Bioinformatics Tools for MGE Analysis (ISfinder, MGfinder)

Module 7: Pangenome Analysis

• Core Genome, Pan-genome, and Accessory Genome

• Pangenome Analysis Methods

• Applications of Pangenome Analysis in Microbiology

• Interpreting Pangenome Results

Module 8: SNP-based Analysis

• Single Nucleotide Polymorphisms (SNPs)

• SNP Detection and Analysis

• Population Genetics and Phylogeography

• Applications of SNP Analysis in Microbiology

Module 9: Phylogenetic Tree Construction

• Principles of Phylogeny

• Phylogenetic Tree Construction Methods (Maximum Likelihood, Neighbor-Joining)

• Tree Visualization and Interpretation

• Phylogenetic Analysis of Microbial Genomes

·  Module 1: Introduction to Genomics and Genetics

• Fundamentals of genetics: DNA structure, inheritance patterns.

• Types of genetic variation: SNPs, indels, CNVs, structural variants.

• Population databases.

• In-silico tools for pathogenicity prediction.

• OMIM database

• NCBI and Ensemble genome browser

·  Module 2: Genome Data Analysis

• Next-generation sequencing technologies.

• Genome alignment and variant calling.

• Variant annotation and filtering: utilizing databases (e.g., dbSNP, ClinVar, gnomAD).

• ACMG/AMP guidelines for variant classification.

• Evaluating evidence from different sources (e.g., population data, functional studies, case reports).

• Writing variant classifications and supporting reports.

• Case studies in variant interpretation.

• Mitochondrial variant interpretation

·  Module 3: Data Visualization and Hands on Practice

• Creating effective visualizations of genomic data (Integrative genome viewer).

• Hands on practice to analyse few cases on third party available tools (raw files will be provided by us)

• Understand the fundamental principles of cytogenetics and its role in human health and disease.

• Learn about the structure, function, and organization of chromosomes.

• Master the techniques of chromosome preparation and banding for karyotype analysis.

• Develop the ability to interpret karyotypes and identify chromosomal abnormalities.

• Understand the principles of microarray technology and its applications in cytogenetics.

• Learn to analyze microarray data and identify copy number variations and other chromosomal abnormalities.

• Gain practical experience in using bioinformatics tools for analyzing cytogenetic data.

• Understand the clinical significance of chromosomal abnormalities and their impact on human health.

Module 1: Primer Design

• Principles of Primer Design

• Factors Affecting Primer Specificity and Efficiency (Melting Temperature, GC content, Secondary Structure)

• Designing Primers for PCR, qPCR, and Sequencing

• Using Primer Design Software (Primer3, OligoAnalyzer)

• Evaluating and Optimizing Primer Design

Module 2: Sanger Sequencing

• Principles of Sanger Sequencing (Chain Termination Method)

• Reading and Interpreting Sequencing Chromatograms

• Identifying Sequencing Errors (Base Calling Errors, Homopolymer Errors)

• Analysis of Sequence Variations (SNPs, Indels)

Module 3: Bioinformatics Tools for Sequence Analysis

• Introduction to Bioinformatics and its applications in molecular biology

• Sequence Analysis Software (BLAST, ClustalW)

• Data Visualization and Interpretation

• Using Online Resources for Sequence Analysis (NCBI, UCSC Genome Browser)

Module 4: DNA Fragment Analysis

• DNA Fragment analysis for chromosomal aneuploidy detection

• Detection of Maternal Cell Contamination in Prenatal Samples