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.
이 강좌는 Genomic Data Science 전문 분야의 일부입니다.
Introduction to Genomic Technologies
제공자:
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 2시간 필요
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".
8개 동영상 (총 81분), 2 readings, 1 quiz
8개의 동영상
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
2개의 읽기 자료
Syllabus10m
Pre-Course Survey10m
1개 연습문제
Quiz 1: Overview and Molecular Biology20m
주
2완료하는 데 1시간 필요
Measurement Technology
In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.
3개 동영상 (총 25분), 1 quiz
1개 연습문제
Quiz 2: Measurement Technology20m
주
3완료하는 데 1시간 필요
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.
6개 동영상 (총 39분), 1 quiz
6개의 동영상
Algorithms4m
Memory and Data Structures6m
Efficiency3m
Software Engineering8m
What is Computational Biology Software11m
1개 연습문제
Quiz 3: Computing Technology20m
주
4완료하는 데 2시간 필요
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.
10개 동영상 (총 55분), 2 readings, 2 quizzes
10개의 동영상
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
2개의 읽기 자료
Course Project Instructions and Reading10m
Post-Course Survey10m
2개 연습문제
Quiz 4: Data Science Technology20m
Course Project20m
4.5
279개의 리뷰36%
이 강좌를 수료한 후 새로운 경력 시작하기
28%
이 강좌를 통해 확실한 경력상 이점 얻기
Introduction to Genomic Technologies의 최상위 리뷰
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.
강사
Steven Salzberg, PhD
ProfessorBiomedical Engineering, Computer Science, and Biostatistics
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
존스홉킨스대학교 정보
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.
Genomic Data Science 전문 분야 정보
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.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.
환불 규정은 어떻게 되나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
Coursera는 세계 최고의 교육에 대한 보편적인 접근 기회를 제공하며,
최고의 대학 및 기관들과 제휴하여 온라인 강좌를 제공합니다.
© 2019 Coursera Inc. All rights reserved.
