About this course: 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.
Created by: Peking University
Taught by: Ge Gao 高歌, Ph.D., Assistant Professor, Principle Investigator
Center for Bioinformatics, School of Life Science
Taught by: Liping Wei 魏丽萍, Ph.D., Professor, Director
Center for Bioinformatics, School of Life Sciences
| Commitment | 1-2 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
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
4 videos, 2 readings
- Video: History of Bioinformatics
- Video: Bioinformatics in Mainland China
- Video: About This Course
- Reading: Readings
- Reading: Slides
Graded: Introduction and History of Bioinformatics
WEEK 2
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.
7 videos, 2 readings
- Video: Global Alignment by Dynamic Programming
- Video: From Global to Local
- Video: Alignment with Affine Gap Penalty and Calculation of Time Complexity of The Needleman-Wunsch Algorithm
- Video: Interview with M. S. Waterman Waterman
- Video: Supplement on Homology & Similarity, Similarity Matrix and Dot Matrix (English Subtitles)
- Video: Student Presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Sequence Alignment
WEEK 3
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.
3 videos, 2 readings
- Video: BLAST Algorithm: A Primer
- Video: Student Presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Sequence Database Search
WEEK 4
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.
4 videos, 2 readings
- Video: Hidden Markov Model
- Video: Predict with Hidden Markov Model
- Video: Student Presentation
- Reading: Readings
- Reading: Slides
Graded: Markov Model
WEEK 5
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.
8 videos, 2 readings
- Video: Reads Mapping and Variants Calling
- Video: Computer Lab: Reads mapping and variant calling (English Subtitles)
- Video: Supplement on reads mapping and variant calling (English Subtitles)
- Video: Supplement on genotyping (English Subtitles)
- Video: A quick tour to sequencer 1 - Ion Torrent PGM (English Subtitles)
- Video: A quick tour to sequencer 2 - 3730 Sanger sequencing (English Subtitles)
- Video: Student presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Next Generation Sequencing (NGS)
WEEK 6
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.
6 videos, 2 readings
- Video: Variant Databases
- Video: Conservation-Based and Rule-Based Methods: SIFT & PolyPhen
- Video: Classifier-Based Methods: SAPRED
- Video: Introduction to Support Vector Machine(SVM) (English Subtitles)
- Video: Student presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Functional Prediction of Genetic Variants
WEEK 7
Mid-term Exam
The description goes here
Graded: Mid-term Review
WEEK 8
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.
5 videos, 2 readings
- Video: RNA-Seq: Mapping & Assembling
- Video: Computer Lab: RNA-seq Data Analysis RNA-seq (English Subtitles)
- Video: Dr. Maynard Olson Talk
- Video: Student presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Next Generation Sequencing: Transcriptome Analysis, and RNA-Seq
WEEK 9
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.
6 videos, 2 readings
- Video: Data Mining: Identify long ncRNAs
- Video: Data Mining: Differential Expression and Clustering
- Video: Feature selection and Clustering (English Subtitles)
- Video: A quick tour to sequencer - illumina HiSeq & MiSeq (English Subtitles)
- Video: Student Presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Prediction and Analysis of Noncoding RNA
WEEK 10
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.
8 videos, 2 readings
- Video: KEGG Pathway Database
- Video: Annotations in Gene Ontology
- Video: Pathway Identification
- Video: An Application: Common Molecular Pathways Underlying Addiction
- Video: Brief Introduction to Database (English Subtitles)
- Video: KOBAS Demo (English Subtitles)
- Video: Student presentation on KOBAS (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Ontology and Identification of Molecular Pathways
WEEK 11
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.
6 videos, 1 reading
- Video: National Center for Biotechnology Information
- Video: European Bioinformatics Institute
- Video: UCSC Genome Browser
- Video: Individual Resources
- Video: CBI Resources Review (English Subtitles)
- Reading: Slides
Graded: Bioinformatics Database and Software Resources
WEEK 12
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.
5 videos, 2 readings
- Video: New Gene Evolution Detected by Genomic Computation: A Driver for Human Brain Evolution
- Video: A Human-Specific de novo Gene Associated with Addiction
- Video: Origination of de novo Genes from Noncoding RNAs
- Video: Student Presentation (English Subtitles)
- Reading: Readings
- Reading: Slides
Graded: Origination of New Genes
WEEK 13
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.
5 videos, 1 reading
- Video: Project background introduction by Dr. Gang Pei
- Video: From Dry to Wet, an Evolutionary Story Part 2
- Video: Talk with Dr. Gang Pei (English Subtitles)
- Video: Student Presentation (English Subtitles)
- Reading: Slides
WEEK 14
Final Exam
The description goes here
Graded: Final Exam
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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.
Founded in 1898, Peking University (PKU) was the first national comprehensive university in China. For the past 115 years, with its hundreds of thousands of outstanding alumni, Peking University has made prominent contributions in the humanities and sciences to further China's prosperity and progress.
Ratings and Reviews
GOOD
this is a good course from china
课程很好，很多东西，对今后的研究工作恩达的帮助！
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JZ
the first part is very good for beginners but not so good in later parts