Learning Paths

Guided roadmaps to master bioinformatics skills, from beginner foundations to advanced specialization.

Bioinformatics Foundations

Beginner

Start here if you have a biology background and want to learn computational skills, or vice versa.

1. Core Biology & Genetics

Understand the Central Dogma, DNA structure, and basic genetics.

Khan Academy Biology Molecular Biology of the Cell

2. Linux & Command Line

Master the terminal, file manipulation, and bash scripting.

Command Line Bootcamp Rosalind: Python Village

3. Python or R Programming

Learn a scripting language for data analysis.

Python for Biologists Bioinformatics with Python (Coursera)

Genomic Data Analyst

Intermediate

Master the skills needed to analyze NGS data, variants, and gene expression.

1. NGS Fundamentals

FASTQ formats, quality control (FastQC), and trimming.

Galaxy Project Tutorials

2. Alignment & Variant Calling

Mapping reads (BWA, Bowtie2) and identifying mutations (GATK).

GATK Best Practices

3. RNA-Seq Analysis

Differential expression analysis using R (DESeq2, edgeR).

RNA-seqlopedia

Computational Biologist / Developer

Advanced

Build tools, pipelines, and algorithms for biological data.

1. Algorithm Design

Dynamic programming, graph theory, and string algorithms.

Algorithms for DNA Sequencing

2. Workflow Managers

Scalable pipelines with Nextflow or Snakemake.

Nextflow Training

3. Cloud & Containerization

Docker, Singularity, and AWS/Google Cloud Life Sciences.

Biocontainers

AI in Biology Specialist

Advanced

Apply machine learning and deep learning to biological problems.

1. Machine Learning Basics

Supervised/unsupervised learning, scikit-learn.

Machine Learning (Andrew Ng)

2. Deep Learning for Bio

Neural networks for sequence analysis (CNNs, RNNs, Transformers).

DeepCHEM

3. Structural Biology & AlphaFold

Protein structure prediction and interaction modeling.

AlphaFold Database