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Learn Bioinformatics, earn certificates with free online courses from Harvard, Stanford, MIT, University of Michigan and other top universities around the world. Read reviews to decide if a class is right for you.
Explore DNA's hidden messages using computational biology. Learn algorithms to identify replication origins and molecular clocks in bacterial genomes. Apply motif-finding software to real biological data.
Learn Python programming fundamentals and apply them to data analysis, web scraping, and database management for practical informatics applications.
This course will cover the topic of Whole genome sequencing (WGS) of bacterial genomes which is becoming more and more relevant for the medical sector.
Learn Python programming through bioinformatics, solving real biological problems and implementing algorithms. Ideal for beginners interested in computational biology and DNA analysis.
Comprehensive bioinformatics course covering sequencing technologies, RNA-seq analysis, clustering methods, single-cell genomics, epigenetics, GWAS, and cancer genomics. Emphasizes computational techniques and data analysis in modern biology.
This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
Comprehensive exploration of computational biology, covering microarrays, RNA-seq, ChIP-seq, epigenetics, GWAS, cancer genomics, and deep learning, with hands-on data analysis techniques.
Comprehensive lecture series on statistical methods for analyzing genomic data, covering microarrays, RNA-seq, epigenetics, cancer genomics, and more. Focuses on practical applications in bioinformatics and computational biology.
Explore the intersection of DNA and AI, focusing on ALS research and drug development, with insights on neurodegeneration and career advice in biotech.
Explore cutting-edge computational biology projects at MIT, covering topics like epigenetics, protein structures, gene expression, machine learning in cancer research, and more.
Explore deep learning applications in genomics, from neural networks to single-cell analysis. Gain insights into regulatory genomics, epigenomics, and genetics through advanced computational techniques.
Explore genome sequencing and antibiotic analysis using graph theory and brute force algorithms. Learn to assemble genomes, sequence antibiotics, and apply bioinformatics tools to real-world pathogens.
Explore genome comparison techniques, from aligning genes to analyzing large-scale mutations. Learn dynamic programming and combinatorial algorithms to study species evolution and genome fragility.
Explore genomic data clustering techniques for gene expression analysis and human migration patterns. Learn algorithms for data point grouping and dimensionality reduction using principal components analysis.
Explore BaseSpace platform for bioinformatics applications: genome assembly, RNA-Seq analysis, and sequencing comparisons. Optional: Build your own genome assembler for real-world data.
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