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Introduction to Genomic Technologies

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.

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What's inside

Syllabus

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".

Measurement Technology

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

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.

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds foundational knowledge in genomics and sequencing technologies

Provides a comprehensive introduction to the field

Covers the essential concepts of next-generation sequencing

Introduces key concepts in computing and data science

Requires no prior knowledge in molecular biology or computer science

Taught by experienced instructors in genomics and data science

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Reviews summary

Essential genomics skills

Learners say this introductory course is largely positive. It provides a well received overview of genomics technologies. Course content is engaging but some topics, like the statistics section, can be difficult. Instructors are experts in the genomics field and present key concepts in an understandable, interesting way. Students with a basic understanding of biology, statistics, and computer science will find the course easier to navigate. A large majority of students highly recommend this course for anyone interested in learning about genomics technologies. Students report that this course is a good foundation for further study in genomics or related fields. They report learning about key concepts such as DNA sequencing, bioinformatics, and genomics data analysis. Many students appreciated the hands-on nature of the course, which included quizzes, assignments, and a course project.

Features engaging video lectures that make learning genomics concepts more enjoyable.

"I really gained the perfect insight on genetic and genomics "

"I love the course as introduction to data science."

"Fantastic course. Explanations are as lucid as they can be. Instructors are amazingly captivating and enthusiastic."

Breaks down complex genomics concepts into digestible parts for easier understanding.

"It was a very good introduction, especially liked the week4 statistics part and the final course project, extremely useful."

"Even though most of the information in this course was familiar to me, I really enjoyed reviewing some concepts and learning new things. Thank you so much! "

"Great intro course if you already have a strong bioinformatics/ statistics background. Easy to get through and refresh your knowledge of computational bio."

Taught by renowned experts in genomics research and data science.

"It was well taught. I liked the fact the two professors focused on two different subjects- biology and statistics portion of this course."

"The instructors were amazing and the knowledge I gained helped me alot in clearing many misconceptions. "

"Excellent course. It can be very useful even for beginners. Although introductory, it manages to offer a good depth of concepts."

"Really enjoy the course. Steven and Jeffrey are both great lecturers and I like the way they make complicated knowledge into smaller, easier pieces. "

Delivers an organized introduction to genomics with an emphasis on its technologies, applications, and statistical components.

"This course have helped me get ready for the next step in my career."

"It is a good course for me because we are planning to put up a molecular biology laboratory in my Department."

"All in all, I think this is a great beginner course for all kinds of students or post-graduate individuals that want to keep on learning and maintain skill sets that are not only great for staying up-to-date, but also putting ourselves in better positions for the future."

Assumes some familiarity with biology, computer science, and statistics, which may be a barrier for learners without these backgrounds.

"not worth the time for a person having a biology background. "

"This course touches very basic points and its good for refreshment if you already know these topics, not so good if you are new in the field."

May feel too brief for some learners, especially those with little to no background in genomics.

"This course covers topics very superficially. Hopefully the next courses in the specialization go more in-depth. I did learn some things, but most of the stuff covered was very basic."

"The computer science part comes only in the last part of the course, the content could definitely be enhanced with the inclusion of few latest technology information and developed research paper for project work (current project work paper is 21-years-old)"

Though difficult for some, the statistics section provides valuable insights into the role of statistical analysis in genomics research.

"The statistics part was too fast needs more details"

"It was unbalanced the workload of the last week of the course compared to the three previous week."

"Decent. There are some strange trivial errors in some of the questions."

"The four modules of the course are well suited for an introduction. For graduates in biology the questions might be a bit too easy (especially considering you can take the test again after reviewing the lectures). The last part with the genomics paper might be too hard because it includes some genetics concepts that have never been talked about in the lectures."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Genomic Technologies with these activities:

Review Basic Biology Knowledge

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Reviewing basic biology concepts will provide a solid foundation for understanding genomics.

Browse courses on Molecular Biology

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Read through introductory biology textbooks or online resources.
Take practice quizzes or tests to assess your understanding.

Review 'Introduction to Genomics' by Peter J. Russell

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This book provides a comprehensive overview of genomics, its applications, and ethical implications.

View Biology: The Dynamic Science (MindTap Course... on Amazon

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Read through the chapters relevant to the course topics.
Take notes and highlight key concepts.
Discuss the book's content with peers or the instructor.

Follow Tutorials on Next-Generation Sequencing

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Tutorials provide hands-on experience and practical knowledge of next-generation sequencing techniques.

Browse courses on Next-Generation Sequencing

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Identify reputable online platforms or courses offering tutorials.
Work through the tutorials, following the instructions and completing exercises.
Experiment with different parameters and settings to gain a deeper understanding.

Four other activities

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Participate in Study Groups

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Engaging with peers through study groups can foster collaboration, knowledge sharing, and critical thinking.

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Connect with classmates or form study groups.
Meet regularly to discuss course materials, share insights, and work through problems.
Provide constructive feedback and support to group members.

Practice Solving Bioinformatics Problems

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Solving bioinformatics problems strengthens computational thinking and problem-solving skills essential for genomics research.

Browse courses on Bioinformatics

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Identify online platforms or resources with bioinformatics problems.
Attempt to solve problems independently.
Review solutions and learn from your mistakes.

Develop a Data Analysis Plan

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Creating a data analysis plan will help you organize and structure your approach to analyzing genomic data.

Browse courses on Data Analysis

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Define the research question and objectives.
Identify the relevant data sources and types.
Choose appropriate data analysis methods and tools.
Document your plan clearly and concisely.

Create Visualizations of Genomic Data

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Creating visual representations of genomic data enhances understanding and facilitates communication of complex information.

Browse courses on Data Visualization

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Choose a dataset and identify key patterns or trends.
Explore different visualization techniques and platforms.
Create compelling visuals that effectively convey the data.
Share your visualizations with others for feedback and discussion.

Career center

Learners who complete Introduction to Genomic Technologies will develop knowledge and skills that may be useful to these careers:

Computational Biologist

A Computational Biologist uses computer science and mathematics to solve biological problems. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Computational Biologist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Computational Biologist

Bioinformatician

A Bioinformatician analyzes biological data, such as DNA sequences, to identify patterns and trends. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Bioinformatician. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Bioinformatician

Molecular Biologist

A Molecular Biologist studies the structure and function of molecules. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Molecular Biologist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Molecular Biologist

Medical Geneticist

A Medical Geneticist studies the role of genes in health and disease. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Medical Geneticist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Medical Geneticist

Pharmacogenomics Scientist

A Pharmacogenomics Scientist studies the role of genes in drug response. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Pharmacogenomics Scientist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Pharmacogenomics Scientist

Population Geneticist

A Population Geneticist studies the genetic diversity of populations. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Population Geneticist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Population Geneticist

Research Scientist

A Research Scientist conducts scientific research in a variety of fields. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Research Scientist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

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Geneticist

A Geneticist studies genes and heredity. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Geneticist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Geneticist

Data Scientist

A Data Scientist uses data to solve problems and make decisions. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Data Scientist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

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Science Writer

A Science Writer writes about scientific topics for a variety of audiences. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Science Writer. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

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Technical Writer

A Technical Writer writes technical documents, such as manuals and reports. This course may be helpful for a Technical Writer who wants to learn more about the basic biology of modern genomics and the experimental tools used to measure it. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

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Web Developer

A Web Developer develops and maintains websites. This course may be helpful for a Web Developer who wants to learn more about the basic biology of modern genomics and the experimental tools used to measure it. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Web Developer

Statistician

A Statistician collects, analyzes, interprets, and presents data. This course may be helpful for a Statistician who wants to learn more about the basic biology of modern genomics and the experimental tools used to measure it. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

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Teacher

A Teacher teaches students about a variety of subjects. This course may be helpful for a Teacher who wants to learn more about the basic biology of modern genomics and the experimental tools used to measure it. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Teacher

Systems Biologist

A Systems Biologist studies the interactions between different parts of a biological system. This course provides a strong foundation in the basic biology of modern genomics and the experimental tools used to measure it, which are essential skills for a Systems Biologist. The course also covers key concepts in computing and data science, which are necessary for understanding how data from next-generation sequencing experiments are generated and analyzed.

See salaries and explore the career path for Systems Biologist

Reading list

We've selected 17 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Genomic Technologies.

Genomes 4

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This introductory textbook covers eukaryotic genomes comprehensively, including the latest advances in the field.

Introduction to Genomic Technologies

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Essential genomics skills

Activities

Career center

Reading list

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