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Bioinformatics: Introduction and Methods 生物信息学: 导论与方法
Course
en
English
14 h
This content is rated 0 out of 5
- Self-paced
- Free Access
- Fee-based Certificate
- 14 Sequences
- Introductive Level
Course details
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. O... - 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 p... - 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. - 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. - 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 analyz... - 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 p... - Week 7 - Mid-term Exam
The description goes here - 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. - 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. - 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. - 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; associat... - 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 s... - 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 Scie... - Week 14 - Final Exam
The description goes here
Prerequisite
None.
Instructors
Ge Gao 高歌, Ph.D.
Assistant Professor, Principle Investigator
Center for Bioinformatics, School of Life Science
Liping Wei 魏丽萍, Ph.D.
Professor, Director
Center for Bioinformatics, School of Life Sciences
Editor
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.
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
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