Genomic Data

 

 


 

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E.g., 2016-12-10
E.g., 2016-12-10
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Nov 21st 2016

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.

Average: 7.8 (8 votes)
Nov 21st 2016

Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Average: 9 (1 vote)
Nov 21st 2016

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.

Average: 2.9 (7 votes)
Nov 21st 2016

An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Average: 6.8 (4 votes)
Nov 21st 2016

Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.

Average: 8.3 (3 votes)
Nov 21st 2016

Learn to use the tools that are available from the Galaxy Project. This is the second course in the Genomic Big Data Science Specialization.

Average: 1 (4 votes)
Nov 7th 2016

Learn how developments in genomics are transforming our knowledge and treatment of conditions such as diabetes. There have been huge advances in the field of genetics in the last 10 years since the sequencing of the first human genome in 2003. It is now possible to analyse all 20,000 human genes in a single experiment, rather than focussing on one gene at a time. We are in the genomics era.

Average: 9 (1 vote)
May 23rd 2016

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters.

Average: 7.6 (5 votes)