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.
This is the first course in the Genomic Data Science Specialization.
Este curso forma parte de Programa Especializado - Genomic Data Science
Introduction to Genomic Technologies
ofrecido por
Acerca de este Curso
4.5
1,332 calificaciones
Habilidades que obtendrás
BioinformaticsStatisticsData ScienceComputational Biology
Programa - Qué aprenderás en este curso
Semana
1Overview
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".
8 videos (Total 81 min), 2 readings, 1 quiz
8 videos
What Is Genomics?7m
What Is Genomic Data Science?8m
Just Enough Cell Biology8m
Important Molecules in Molecular Biology7m
The Human Genome Project17m
Molecular Biology Structures9m
From Genes to Phenotypes9m
2 lecturas
Syllabus10m
Pre-Course Survey10m
1 ejercicio de práctica
Quiz 1: Overview and Molecular Biology20m
Semana
2Measurement Technology
In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.
3 videos (Total 25 min), 1 quiz
1 ejercicio de práctica
Quiz 2: Measurement Technology20m
Semana
3Computing Technology
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.
6 videos (Total 39 min), 1 quiz
6 videos
Algorithms4m
Memory and Data Structures6m
Efficiency3m
Software Engineering8m
What is Computational Biology Software11m
1 ejercicio de práctica
Quiz 3: Computing Technology20m
Semana
4Data Science Technology
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.
10 videos (Total 55 min), 2 readings, 2 quizzes
10 videos
What Went Wrong?4m
The Central Dogma of Statistics3m
Data Sharing Plans4m
Getting Help with Statistics2m
Plotting Your Data5m
Sample Size and Variability7m
Statistical Significance6m
Multiple Testing7m
Study Design, Batch Effects, and Confounding7m
2 lecturas
Course Project Instructions and Reading10m
Post-Course Survey10m
2 ejercicios de práctica
Quiz 4: Data Science Technology20m
Course Project20m
30%
comenzó una nueva carrera después de completar estos cursos
83%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Principales revisiones
por KK•Nov 21st 2017
Relatively nice introduction course, contents are maybe rather limited, yet as an instructive course, it does provide a clear overview which correlates well with the required answers for the quizzes!
por MR•Jun 13th 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.
Instructores
Steven Salzberg, PhD
ProfessorBiomedical Engineering, Computer Science, and Biostatistics
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Acerca de Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Acerca del programa especializado Genomic Data Science
This specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, Python, R, Bioconductor, and Galaxy. The sequence is a stand alone introduction to genomic data science or a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics.
To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit.
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