ABI Bioinformatics Guide 2024
  • INTRODUCTION
    • How to use the guide
  • MOLECULAR BIOLOGY
    • The Cell
      • Cells and Their Organelles
      • Cell Specialisation
      • Quiz 1
    • Biological Molecules
      • Carbohydrates
      • Lipids
      • Nucleic Acids (DNA and RNA)
      • Quiz 2
      • Proteins
      • Catalysis of Biological Reactions
      • Quiz 3
    • Information Flow in the Cell
      • DNA Replication
      • Gene Expression: Transcription
      • Gene Expression: RNA Processing
      • Quiz 4
      • Chromatin and Chromosomes
      • Regulation of Gene Expression
      • Quiz 5
      • The Genetic Code
      • Gene Expression: Translation
    • Cell Cycle and Cell Division
      • Quiz 6
    • Mutations and Variations
      • Point mutations
      • Genotype-Phenotype Interactions
      • Quiz 7
  • PROGRAMMING
    • Python for Genomics
    • R programming (optional)
  • STATISTICS: THEORY
    • Introduction to Probability
      • Conditional Probability
      • Independent Events
    • Random Variables
      • Independent, Dependent and Controlled Variables
    • Data distribution PMF, PDF, CDF
    • Mean, Variance of a Random Variable
    • Some Common Distributions
    • Exploratory Statistics: Mean, Median, Quantiles, Variance/SD
    • Data Visualization
    • Confidence Intervals
    • Comparison tests, p-value, z-score
    • Multiple test correction: Bonferroni, FDR
    • Regression & Correlation
    • Dimentionality Reduction
      • PCA (Principal Component Analysis)
      • t-SNE (t-Distributed Stochastic Neighbor Embedding)
      • UMAP (Uniform Manifold Approximation and Projection)
    • QUIZ
  • STATISTICS & PROGRAMMING
  • BIOINFORMATICS ALGORITHMS
    • Introduction
    • DNA strings and sequencing file formats
    • Read alignment: exact matching
    • Indexing before alignment
    • Read alignment: approximate matching
    • Global and local alignment
  • NGS DATA ANALYSIS & FUNCTIONAL GENOMICS
    • Experimental Techniques
      • Polymerase Chain Reaction
      • Sanger (first generation) Sequencing Technologies
      • Next (second) Generation Sequencing technologies
      • The third generation of sequencing technologies
    • The Linux Command-line
      • Connecting to the Server
      • The Linux Command-Line For Beginners
      • The Bash Terminal
    • File formats, alignment, and genomic features
      • FASTA & FASTQ file formats
      • Basic Unix Commands for Genomics
      • Sequences and Genomic Features Part 1
      • Sequences and Genomic Features Part 2: SAMtools
      • Sequences and Genomic Features Part 3: BEDtools
    • Genetic variations & variant calling
      • Genomic Variations
      • Alignment and variant detection: Practical
      • Integrative Genomics Viewer
      • Variant Calling with GATK
    • RNA Sequencing & Gene expression
      • Gene expression and how we measure it
      • Gene expression quantification and normalization
      • Explorative analysis of gene expression
      • Differential expression analysis with DESeq2
      • Functional enrichment analysis
    • Single-cell Sequencing and Data Analysis
      • scRNA-seq Data Analysis Workflow
      • scRNA-seq Data Visualization Methods
  • FINAL REMARKS
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  • A Bioinformatics Guide by the Armenian Bioinformatics Institute
  • Who Is The Guide For?
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INTRODUCTION

NextHow to use the guide

Last updated 5 months ago

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A Bioinformatics Guide by the Armenian Bioinformatics Institute

Contemporary medicine, pharmaceuticals, and biotechnology have become increasingly data-driven fields, where the analysis of large-scale biological data serves as a cornerstone of progress and innovation. Revolutionary technologies, such as high-throughput sequencing, have transformed bio-related research and industries. However, these advances have also highlighted a critical gap: the shortage of specialists—bioinformaticians—who can convert vast datasets into actionable insights. Training experts in bioinformatics and genomics is therefore essential for advancing life sciences research.

To address this need, the Armenian Bioinformatics Institute (ABI, ), in collaboration with the Bioinformatics Group at the Institute of Molecular Biology (IMB) NAS RA, has initiated an annual series of summer schools in genome bioinformatics. To extend the reach of these efforts, we have compiled the materials from these schools into this guide.

This guide provides you with the foundational knowledge and skills needed to embark on your first bioinformatics project. While this is not an exhaustive resource, it serves as a starting point, equipping you with the tools and inspiration to pursue further education in this dynamic field.

Who Is The Guide For?

This guide is designed for biologists or data/computer scientists eager to embark on their journey in Bioinformatics and Genomics. However, if you do not fit into these categories but are still interested in exploring the fascinating world of science, we encourage you to challenge yourself and complete the guide. Lack of prior knowledge in either discipline should not hinder your progress (see details below).

The guide encompasses fundamental aspects of Molecular Biology, Programming in R and Python, basics of Unix command-line, Statistics, Experimental Techniques in Genetics and Genomics, Bioinformatics algorithms, Sequencing data analysis and Functional Genomics.

Advanced access and certification

We provide free access to this guide for anyone interested in starting their journey in bioinformatics. If you find our work valuable, we encourage you to support the Armenian Bioinformatics Institute with a donation. As a non-profit organization, your contributions help us continue developing training materials and resources.

To donate, visit:

Thank you for supporting our mission to advance bioinformatics education!

Credits

This guide includes both original content and links to external resources. The original content is authored by:

  • Created by the ABI team

    • Final editing by: Maria Nikoghosyan and Lilit Nersisyan, PhD

  • Original content in specific modules created by:

    • Aleksey Kurnosov, PhD (Molecular Biology)

    • Vahan Huroyan, PhD (Statistics)

    • Susanna Avagyan (Single-cell gene expression data analysis)

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