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

Peking University via Coursera

Go to Course: https://www.coursera.org/learn/bioinformatics-pku

Introduction

## Course Review: Bioinformatics: Introduction and Methods (生物信息学: 导论与方法) In today's world of rapid advancements in scientific technology, bioinformatics plays a crucial role in decoding the vast amounts of biological data generated every day. “Bioinformatics: Introduction and Methods,” offered by Peking University on Coursera, is a well-structured and comprehensive course designed for individuals looking to delve into this interdisciplinary field. This course not only introduces the fundamental concepts of bioinformatics but also provides hands-on experience with computational methods and tools that are essential for future study and research. ### Course Overview The course begins with an engaging introduction to bioinformatics, exploring its history and significance in modern biology. As you progress through the modules, you will learn about various computational methods, from sequence alignment algorithms to the intricacies of next-generation sequencing (NGS). Each section is designed to equip you with both theoretical knowledge and practical skills, making it an excellent resource for students and professionals alike. ### Syllabus Highlights 1. **Introduction and History of Bioinformatics**: This module lays a solid foundation by familiarizing you with essential concepts and the rapid growth of the field. It’s crucial to understand the context and evolution of bioinformatics as it sets the stage for the subsequent content. 2. **Sequence Alignment**: You’ll learn about dynamic programming algorithms like Needleman-Wunsch and Smith-Waterman. The course offers a unique opportunity to witness the discovery process of the Smith-Waterman algorithm through insights from Dr. Michael Waterman himself. 3. **Sequence Database Search**: This module introduces you to vital databases and the BLAST algorithm. You’ll gain skills to adjust BLAST parameters specifically tailored to your research needs. 4. **Markov Model**: Here, you will delve into Markov chains and hidden Markov models, acquiring the ability to create predictive models applicable to biological problems. 5. **Next Generation Sequencing (NGS)**: One of the highlights of this course, this module covers read mapping and variant calling, essential skills in contemporary genomic studies. Learning how to analyze real NGS data using bioinformatic tools is invaluable. 6. **Functional Prediction of Genetic Variants**: You’ll explore variant prediction tools like SIFT, Polyphen, and others, enabling you to apply these tools to real research problems. 7. **Ontology and Identification of Molecular Pathways**: This module focuses on understanding gene ontology and utilizing databases like KEGG for pathway analysis, enhancing your ability to contextualize genetic data. 8. **Case Studies**: The course features compelling case studies, including the origination of new genes and the analysis of DNA methyltransferases, providing practical applications of the concepts learned. ### Assignments and Exams The course includes mid-term and final exams, which are designed to test your understanding of the material covered. These assessments reinforce the knowledge gained and ensure that you can apply the concepts in practical scenarios. ### Recommendation I wholeheartedly recommend "Bioinformatics: Introduction and Methods" if you're interested in bioinformatics, whether you're a student, a researcher, or a professional in a relevant field. The course is ideal for anyone looking to build a solid understanding of bioinformatics, complete with practical applications and the latest methodologies. The instructional quality is enhanced by contributions from esteemed faculty members and real-world experts in the field, providing unique insights that you won't find in textbooks. Moreover, the supplementary materials are valuable resources to deepen your comprehension, even though they’re optional for quizzes or exams. ### Conclusion Enrolling in this course will not only enhance your knowledge but also provide you with essential skills that are increasingly valuable in the scientific community. With a mix of theoretical grounding and hands-on experience, it’s a perfect stepping stone for anyone looking to explore the fascinating world of bioinformatics. Embrace this opportunity to elevate your understanding and stay ahead in this rapidly evolving field!

Syllabus

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

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.

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.

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.

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.

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.

Mid-term Exam

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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.

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.

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.

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.

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.

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.

Final Exam

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