MOOCs & Blogs on Computational Biology and Bioinformatics

Here is the list of Massive Open Online Courses (MOOCs) useful for people who are interested to learn about Computational Biology and Bioinformatics.

Basic Python Programming

• Introduction To Python
• Python for Everybody
• Python for Biologists I
• Python for Biologists I
• Introduction To Algorithms and Data Structures

Bioinformatics and Computational Biology

• Bioinformatics Algorithms I

• Bioinformatics Methods I

• Bioinformatics Methods II

• Finding Hidden Messages in DNA (Bioinformatics I)

• Genome Sequencing (Bioinformatics II)

• Comparing Genes, Proteins, and Genomes (Bioinformatics III)

• Deciphering Molecular Evolution (Bioinformatics IV)

• Finding Mutations in DNA and Proteins (Bioinformatics VI)

• Genes and the Human Condition (From Behavior to Biotechnology)

• Case study: RNA-seq data analysis

• Case study: Variant Discovery and Genotyping

• Case study: ChIP-seq data analysis

• Case study: DNA methylation data analysis

• Genomic Data Science with Galaxy

Algorithm and Programming

• Algorithms, Biology, and Programming for Beginners

• Python for Genomic Data Science

• Command Line Tools for Genomic Data Science

• Algorithms for DNA Sequencing

• Bioconductor for Genomic Data Science

• Introduction to Bioconductor

Introduction to Biology and Molecular Biology

• Introduction to Biology - The Secret of Life

• DNA: Biology’s Genetic Code

• Molecular Biology - Part 1: DNA Replication and Repair

• Molecular Biology – Part 2: Transcription and Transposition

Genomics, Epigenomics

• Introduction to Genomic Technologies

• Epigenetic Control of Gene Expression

• Experimental Genome Science

• Genomic Medicine Gets Personal

• Cancer in the 21st Century: The Genomic Revolution

• Data Analysis for Genomics

Systems Biology

• Introduction to Systems Biology

• Experimental Methods in Systems Biology

• Network Analysis in Systems Biology

• Dynamical Modeling Methods for Systems Biology

• Integrated Analysis in Systems Biology

Machine Learning

• Machine Learning, by Andrew Ng, Stanford University

• Learning from Data, by Yaser S. Abu-Mostafa, California Institute of Technology.

• Introduction to Linear Models and Matrix Algebra, Harvard University

• Genomic Data Science and Clustering (Bioinformatics V) , University of California, San Diego

Statistics for Life Science

• Statistics and R for the Life Sciences

• Advanced Statistics for the Life Sciences

• Statistics for Genomic Data Science

Specilization Courses on Coursera

• Bioinformatics, University of California, San Diego

• Genomic Data Science, Johns Hopkins University

• Systems Biology, Icahn School of Medicine at Mount Sinai