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 faz parte do Programa de cursos integrados Análise de Dados GenômicosAnálise Genômica
Introdução à Tecnologia Genômica
oferecido por
Informações sobre o curso
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Habilidades que você terá
BioinformaticsStatisticsData ScienceComputational Biology
Programa - O que você aprenderá com este curso
Semana
12 horas para concluir
Overview
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 vídeos (Total 81 mín.), 2 leituras, 1 teste
8 videos
Why Genomics?12min
What Is Genomics?7min
What Is Genomic Data Science?8min
Just Enough Cell Biology8min
Important Molecules in Molecular Biology7min
The Human Genome Project17min
Molecular Biology Structures9min
From Genes to Phenotypes9min
2 leituras
Syllabus10min
Pre-Course Survey10min
1 exercício prático
Quiz 1: Overview and Molecular Biology20min
Semana
21 hora para concluir
Measurement Technology
In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.
3 vídeos (Total 25 mín.), 1 teste
1 exercício prático
Quiz 2: Measurement Technology20min
Semana
31 hora para concluir
Computing 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 vídeos (Total 39 mín.), 1 teste
6 videos
Algorithms4min
Memory and Data Structures6min
Efficiency3min
Software Engineering8min
What is Computational Biology Software11min
1 exercício prático
Quiz 3: Computing Technology20min
Semana
42 horas para concluir
Data 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 vídeos (Total 55 mín.), 2 leituras, 2 testes
10 videos
What Went Wrong?4min
The Central Dogma of Statistics3min
Data Sharing Plans4min
Getting Help with Statistics2min
Plotting Your Data5min
Sample Size and Variability7min
Statistical Significance6min
Multiple Testing7min
Study Design, Batch Effects, and Confounding7min
2 leituras
Course Project Instructions and Reading10min
Post-Course Survey10min
2 exercícios práticos
Quiz 4: Data Science Technology20min
Course Project20min
36%
comecei uma nova carreira após concluir estes cursos
28%
consegui um benefício significativo de carreira com este curso
Principais avaliações do Introdução à Tecnologia Genômica
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!
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.
Instrutores
Steven Salzberg, PhD
ProfessorBiomedical Engineering, Computer Science, and Biostatistics
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Sobre Universidade Johns Hopkins
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.
Sobre Programa de cursos integrados Análise de Dados GenômicosAnálise Genômica
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.
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, along with a variety of software implementation tools like Python, R, Bioconductor, and Galaxy.
This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.
To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit. Please note that you will not receive a Certificate of Completion if you choose to Audit.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Qual é a política de reembolso?
Existe algum auxílio financeiro disponível?
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