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Ge Gao 高歌, Ph.D. +1 more instructor

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Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

Peking University

About this Course

29,961 recent views

A big welcome to “Bioinformatics: Introduction and Methods” from Peking University! In this MOOC you will become familiar with the concepts and computational methods in the exciting interdisciplinary field of bioinformatics and their applications in biology, the knowledge and skills in bioinformatics you acquired will help you in your future study and research.
Course materials are available under the CC BY-NC-SA License.

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Approx. 25 hours to complete

English

Subtitles: French, Portuguese (European), Russian, English, Spanish

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Approx. 25 hours to complete

English

Subtitles: French, Portuguese (European), Russian, English, Spanish

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.23/5 (30 Ratings)

Ge Gao 高歌, Ph.D.

Assistant Professor, Principle Investigator

Center for Bioinformatics, School of Life Science

47,164 Learners

2 Courses

Liping Wei 魏丽萍, Ph.D.

Professor, Director

Center for Bioinformatics, School of Life Sciences

47,164 Learners

2 Courses

Offered by

Peking University

Peking University is determined to make its education openly accessible to students in China and around the world. With over 3000 faculty members, Peking University offers excellence in teaching and learning.

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Syllabus - What you will learn from this course

Content Rating94%(2,259 ratings)

Week

Week 1

2 hours to complete

Introduction and History of Bioinformatics

Welcome to “Bioinformatics: Introduction and Methods! Upon completion of this module you will be able to: become familiar with the essential concepts of bioinformatics; explore the history of this young area; experience how rapidly bioinformatics is growing. Our supplementary materials will give you a better understanding of the course lectures through they are not required in quizzes or exams

2 hours to complete

4 videos (Total 69 min), 2 readings, 1 quiz

Week

Week 2

2 hours to complete

Sequence Alignment

Upon completion of this module, you will be able to: describe dynamic programming based sequence alignment algorithms; differentiate between the Needleman-Wunsch algorithm for global alignment and the Smith-Waterman algorithm for local alignment; examine the principles behind gap penalty and time complexity calculation which is crucial for you to apply current bioinformatic tools in your research; experience the discovery of Smith-Waterman algorithm with Dr. Michael Waterman himself.

2 hours to complete

7 videos (Total 99 min), 2 readings, 1 quiz

7 videos

Essential Concepts13m

Global Alignment by Dynamic Programming14m

From Global to Local6m

Alignment with Affine Gap Penalty and Calculation of Time Complexity of The Needleman-Wunsch Algorithm6m

Interview with M. S. Waterman Waterman29m

Supplement on Homology & Similarity, Similarity Matrix and Dot Matrix (English Subtitles)10m

Student Presentation (English Subtitles)18m

2 readings

Readings10m

Slides10m

1 practice exercise

Sequence Alignment30m

Week

Week 3

2 hours to complete

Sequence Database Search

Upon completion of this module, you will be able to: become familiar with sequence databse search and most common databases; explore the algoritm behind BLAST and the evaluation of BLAST results; ajdust BLAST parameters base on your own research project.

2 hours to complete

3 videos (Total 41 min), 2 readings, 1 quiz

Week

Week 4

2 hours to complete

Markov Model

Upon completion of this module, you will be able to: recognize state transitions, Markov chain and Markov models; create a hidden Markov model by yourself; make predictuions in a real biological problem with hidden Markov model.

2 hours to complete

4 videos (Total 47 min), 2 readings, 1 quiz

Week

Week 5

2 hours to complete

Next Generation Sequencing (NGS): Mapping of Reads From Resequencing and Calling of Genetic Variants

Upon completion of this module, you will be able to: describe the features of NGS; associate NGS results you get with the methods for reads mapping and models for variant calling; examine pipelines in NGS data analysis; experience how real NGS data were analyzed using bioinformatic tools. This module is required before entering Module 8.

2 hours to complete

8 videos (Total 85 min), 2 readings, 1 quiz

8 videos

From Sequencing to NGS10m

Reads Mapping and Variants Calling14m

Computer Lab: Reads mapping and variant calling (English Subtitles)7m

Supplement on reads mapping and variant calling (English Subtitles)9m

Supplement on genotyping (English Subtitles)18m

A quick tour to sequencer 1 - Ion Torrent PGM (English Subtitles)10m

A quick tour to sequencer 2 - 3730 Sanger sequencing (English Subtitles)3m

Student presentation (English Subtitles)9m

2 readings

Readings10m

Slides10m

1 practice exercise

Next Generation Sequencing (NGS)30m

Week

Week 6

2 hours to complete

Functional Prediction of Genetic Variants

Upon completion of this module you will able to: describe what is variant prediction and how to carry out variant predictions; associate variant databases with your own research projects after you get a list of variants; recognize different principles behind prediction tools and know how to use tools such as SIFT, Polyphen and SAPRED according to your won scientific problem.

2 hours to complete

6 videos (Total 92 min), 2 readings, 1 quiz

Week

Week 7

1 hour to complete

Mid-term Exam

The description goes here

1 hour to complete

Week

Week 8

2 hours to complete

Next Generation Sequencing: Transcriptome Analysis, and RNA-Seq

Upon completion of this module, you will be able to: describe how transcriptome data were generated; master the algorithm used in transcriptome analysis; explore how the RNA-seq data were analyzed. This module is required before entering Module 9.

2 hours to complete

5 videos (Total 67 min), 2 readings, 1 quiz

Week

Week 9

2 hours to complete

Prediction and Analysis of Noncoding RNA

Upon completion of this module, you will be able to: Analyze non-coding RNAs from transcriptome data; identify long noncoding RNA (lncRNA) from NGS data and predict their functions.

2 hours to complete

6 videos (Total 74 min), 2 readings, 1 quiz

Week

Week 10

2 hours to complete

Ontology and Identification of Molecular Pathways

Upon completion of this module, you will be able to: define ontology and gene ontology, explore KEGG pathway databses; examine annotations in Gene Ontology; identify pathways with KOBAS and apply the pipeline to drug addition study.

2 hours to complete

8 videos (Total 95 min), 2 readings, 1 quiz

8 videos

Ontology and Gene Ontology20m

KEGG Pathway Database 10m

Annotations in Gene Ontology 10m

Pathway Identification 22m

An Application: Common Molecular Pathways Underlying Addiction7m

Brief Introduction to Database (English Subtitles)5m

KOBAS Demo (English Subtitles)7m

Student presentation on KOBAS (English Subtitles)9m

2 readings

Readings10m

Slides10m

1 practice exercise

Ontology and Identification of Molecular Pathways30m

Week

Week 11

2 hours to complete

Bioinformatics Database and Software Resources

Upon completion of this module, you will be able to describe the most important bioinformatic resources including databases and software tools; explore both centralized resources such as NCBI, EBI, UCSC genome browser and lots of individual resources; associate all your bioinformatic problems with certain resources to refer to.

2 hours to complete

6 videos (Total 71 min), 1 reading, 1 quiz

Week

Week 12

2 hours to complete

Origination of New Genes

Upon completion of this case study module, you will be able to: experience how to apply bioinformatic data, methods and analyses to study an important problem in evolutionary biology; examine how to detect and study the origination, evolution and function of species-specific new genes; create phylogenetic trees with your own data (not required) with Dr. Manyuan Long, a world-renowned pioneer and expert on new genes from University of Chicago.

2 hours to complete

5 videos (Total 60 min), 2 readings, 1 quiz

5 videos

New Gene Evolution Detected by Genomic Computation: Basic Concepts and Examples20m

New Gene Evolution Detected by Genomic Computation: A Driver for Human Brain Evolution7m

A Human-Specific de novo Gene Associated with Addiction8m

Origination of de novo Genes from Noncoding RNAs11m

Student Presentation (English Subtitles)12m

2 readings

Readings10m

Slides10m

1 practice exercise

Origination of New Genes30m

Week

Week 13

1 hour to complete

Evolution function analysis of DNA methyltransferase

Upon completion of this case study module, you will be able to: experience how to use bioinformatic methods to study the function and evolution of DNA methylases; share with Dr. Gang Pei, president of Tongji University and member of the Chinese Academy of Science, the experiences in scientific research and thought about MOOC.

1 hour to complete

5 videos (Total 71 min), 1 reading

Week

Week 14

1 hour to complete

Final Exam

The description goes here

1 hour to complete

Reviews

4.4

61 reviews

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2 stars
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1 star
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TOP REVIEWS FROM BIOINFORMATICS: INTRODUCTION AND METHODS 生物信息学: 导论与方法

by ASAug 8, 2021

It was a very interesting course and opened up novel and new ways one can think for finding the predictable and the unpredictable properties.

by JSFeb 10, 2020

Advanced technical course. Please also help design courses regarding bioinformatics concepts, applications and tools needed for biology students. Thank you.

by SMAug 17, 2021

That was quit different manner of course in means of quizzes but much informative and great for basic learner specially coursera provide help to cross and understand the language barrior distance

by JZMay 2, 2018

the first part is very good for beginners but not so good in later parts

View all reviews

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Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

About this Course