Bioinformatics: Introduction and Methods 生物信息学: 导论与方法
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Bioinformatics: Introduction and Methods 生物信息学: 导论与方法
Peking University
Informações sobre o curso
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.
Syllabus - What you will learn from this course
1
Section
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 (Total 69 min), 2 readings, 1 quiz
4 videos
History of Bioinformatics30m
Bioinformatics in Mainland China8m
About This Course9m
2 readings
Readings10m
Slides10m
1 practice exercises
Introduction and History of Bioinformatics20m
2
Section
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 (Total 99 min), 2 readings, 1 quiz
7 videos
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 exercises
Sequence Alignment18m
3
Section
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 (Total 41 min), 2 readings, 1 quiz
3 videos
BLAST Algorithm: A Primer13m
Student Presentation (English Subtitles)15m
2 readings
Readings10m
Slides10m
1 practice exercises
Sequence Database Search10m
4
Section
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 (Total 47 min), 2 readings, 1 quiz
4 videos
Hidden Markov Model11m
Predict with Hidden Markov Model10m
Student Presentation16m
2 readings
Readings10m
Slides10m
1 practice exercises
Markov Model 14m
5
Section
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 (Total 85 min), 2 readings, 1 quiz
8 videos
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 exercises
Next Generation Sequencing (NGS)10m
6
Section
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 (Total 92 min), 2 readings, 1 quiz
6 videos
Variant Databases 10m
Conservation-Based and Rule-Based Methods: SIFT & PolyPhen17m
Classifier-Based Methods: SAPRED13m
Introduction to Support Vector Machine(SVM) (English Subtitles)18m
Student presentation (English Subtitles)14m
2 readings
Readings10m
Slides10m
1 practice exercises
Functional Prediction of Genetic Variants14m
7
Section
Mid-term Exam
The description goes here
1 quiz
1 practice exercises
Mid-term Review40m
8
Section
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 (Total 67 min), 2 readings, 1 quiz
5 videos
RNA-Seq: Mapping & Assembling11m
Computer Lab: RNA-seq Data Analysis RNA-seq (English Subtitles)22m
Dr. Maynard Olson Talk9m
Student presentation (English Subtitles)11m
2 readings
Readings10m
Slides10m
1 practice exercises
Next Generation Sequencing: Transcriptome Analysis, and RNA-Seq16m
9
Section
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 (Total 74 min), 2 readings, 1 quiz
6 videos
Data Mining: Identify long ncRNAs10m
Data Mining: Differential Expression and Clustering12m
Feature selection and Clustering (English Subtitles)14m
A quick tour to sequencer - illumina HiSeq & MiSeq (English Subtitles)13m
Student Presentation (English Subtitles)10m
2 readings
Readings10m
Slides10m
1 practice exercises
Prediction and Analysis of Noncoding RNA14m
10
Section
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 (Total 95 min), 2 readings, 1 quiz
8 videos
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 exercises
Ontology and Identification of Molecular Pathways12m
11
Section
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 (Total 71 min), 1 reading, 1 quiz
6 videos
National Center for Biotechnology Information13m
European Bioinformatics Institute 9m
UCSC Genome Browser7m
Individual Resources12m
CBI Resources Review (English Subtitles)8m
1 readings
Slides10m
1 practice exercises
Bioinformatics Database and Software Resources10m
12
Section
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 (Total 60 min), 2 readings, 1 quiz
5 videos
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 exercises
Origination of New Genes10m
13
Section
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 (Total 71 min), 1 reading
5 videos
Project background introduction by Dr. Gang Pei25m
From Dry to Wet, an Evolutionary Story Part 28m
Talk with Dr. Gang Pei (English Subtitles)20m
Student Presentation (English Subtitles)10m
1 readings
Slides10m
14
Section
Final Exam
The description goes here
1 quiz
1 practice exercises
Final Exam20m
Instructors
Ge Gao 高歌, Ph.D.
Assistant Professor, Principle Investigator
Liping Wei 魏丽萍, Ph.D.
Professor, DirectorAbout 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.
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.
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