Introduction to Genomic Technologies

Introduction to Genomic Technologies

This course is part of Genomic Data Science Specialization

Instructors: Steven Salzberg, PhD

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5 assignments

Taught in English

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This course is part of the Genomic Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed.

In this Module, you can expect to study topics of "Just enough molecular biology", "The genome", "Writing a DNA sequence", "Central dogma", "Transcription", "Translation", and "DNA structure and modifications".

What's included

8 videos2 readings1 assignment

8 videosTotal 81 minutes

Why Genomics?13 minutes
What Is Genomics?7 minutes
What Is Genomic Data Science?8 minutes
Just Enough Cell Biology9 minutes
Important Molecules in Molecular Biology8 minutes
The Human Genome Project17 minutes
Molecular Biology Structures9 minutes
From Genes to Phenotypes9 minutes

2 readingsTotal 20 minutes

Syllabus10 minutes
Pre-Course Survey10 minutes

1 assignmentTotal 30 minutes

Quiz 1: Overview and Molecular Biology30 minutes

In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.

What's included

3 videos1 assignment

The lectures for this module cover a few basic topics in computing technology. We'll go over the foundations of computer science, algorithms, memory and data structures, efficiency, software engineering, and computational biology software.

What's included

6 videos1 assignment

In this module on Data Science Technology, we'll be covering quite a lot of information about how to handle the data produced during the sequencing process. We'll cover reproducibility, analysis, statistics, question types, the central dogma of inference, analysis code, testing, prediction, variation, experimental design, confounding, power, sample size, correlation, causation, and degrees of freedom.

What's included

10 videos2 readings2 assignments

10 videosTotal 55 minutes

Why Care About Statistics?4 minutes
What Went Wrong?5 minutes
The Central Dogma of Statistics4 minutes
Data Sharing Plans4 minutes
Getting Help with Statistics3 minutes
Plotting Your Data5 minutes
Sample Size and Variability8 minutes
Statistical Significance6 minutes
Multiple Testing8 minutes
Study Design, Batch Effects, and Confounding8 minutes

2 readingsTotal 20 minutes

Course Project Instructions and Reading10 minutes
Post-Course Survey10 minutes

2 assignmentsTotal 60 minutes

Quiz 4: Data Science Technology30 minutes
Course Project30 minutes

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Instructors

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(832 ratings)

Steven Salzberg, PhD

Johns Hopkins University

2 Courses163,816 learners

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Johns Hopkins University

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Reviewed on Aug 5, 2020

Having a Computer Science background, the course helped me understand the foundational knowledge of Biology and Statistics. The explanations were easy to understand and digest.

Reviewed on May 9, 2022

Thanks to everyone who made this. Such can wait to start the second course. h a superb course; it started slowly and sort of an easy thing, but the last lecture was phenomenal

Reviewed on Jun 12, 2016

Very good introductory course. It's a lot of material to cover for a newbie, but if you have some background, you will find you progress pretty quickly. Enjoyable, engaging, fun and useful.

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