Об этом курсе: 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.
Автор: Johns Hopkins University
Преподаватели: Steven Salzberg, PhD, Professor
Biomedical Engineering, Computer Science, and Biostatistics
Преподаватели: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
| Основные сведения | Курс 1 из 8 — Genomic Data Science Specialization |
| Язык | English |
| Как пройти курс | Чтобы пройти курс, выполните все оцениваемые задания. |
| Оценки пользователей |
Программа курса
НЕДЕЛЯ 1
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 видео, 2 материала для самостоятельного изучения
- Reading: Syllabus
- Reading: Pre-Course Survey
- Видео: What Is Genomics?
- Видео: What Is Genomic Data Science?
- Видео: Just Enough Cell Biology
- Видео: Important Molecules in Molecular Biology
- Видео: The Human Genome Project
- Видео: Molecular Biology Structures
- Видео: From Genes to Phenotypes
Оцениваемый: Quiz 1: Overview and Molecular Biology
НЕДЕЛЯ 2
Measurement Technology
In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.
3 видео
- Видео: Next Generation Sequencing
- Видео: Applications of Sequencing
Оцениваемый: Quiz 2: Measurement Technology
НЕДЕЛЯ 3
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 видео
- Видео: Algorithms
- Видео: Memory and Data Structures
- Видео: Efficiency
- Видео: Software Engineering
- Видео: What is Computational Biology Software
Оцениваемый: Quiz 3: Computing Technology
НЕДЕЛЯ 4
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 видео, 2 материала для самостоятельного изучения
- Видео: What Went Wrong?
- Видео: The Central Dogma of Statistics
- Видео: Data Sharing Plans
- Видео: Getting Help with Statistics
- Видео: Plotting Your Data
- Видео: Sample Size and Variability
- Видео: Statistical Significance
- Видео: Multiple Testing
- Видео: Study Design, Batch Effects, and Confounding
- Reading: Course Project Instructions and Reading
- Reading: Post-Course Survey
Оцениваемый: Quiz 4: Data Science Technology
Оцениваемый: Course Project
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Авторы
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.
Стоимость
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Рейтинги и отзывы
good
A nice overview of all the subfields that make up bioinformatics.
it was interesting course but the part of statistics was severely complicated and should be taught in simple language.
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this was good course. Its really appreciating that you are teaching students sitting at home and learning online. this course was also good but i feel difficulty in learning 4th week course. Especially calculating p value and plotting data . I think that should be more precisely and should be describe with more examples. Thank you so much for this course and for increasing my knowledge.