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

Methode

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

Coursera (CC)
Logo von Coursera (CC)
Bewertung: starstarstarstar_halfstar_border 7,2 Bildungsangebote von Coursera (CC) haben eine durchschnittliche Bewertung von 7,2 (aus 6 Bewertungen)

Tipp: Haben Sie Fragen? Für weitere Details einfach auf "Kostenlose Informationen" klicken.

Beschreibung

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

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 Bioi…

Gesamte Beschreibung lesen

Frequently asked questions

Es wurden noch keine FAQ hinterlegt. Falls Sie Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice. Wir helfen gerne weiter!

Noch nicht den perfekten Kurs gefunden? Verwandte Themen: .

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

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 4.6 stars Average User Rating 4.6See what learners said 课程作业

每门课程都像是一本互动的教科书,具有预先录制的视频、测验和项目。

来自同学的帮助

与其他成千上万的学生相联系,对想法进行辩论,讨论课程材料,并寻求帮助来掌握概念。

证书

获得正式认证的作业,并与朋友、同事和雇主分享您的成功。

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.

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 expand


  1. Video: What is Bioinformatics
  2. Video: History of Bioinformatics
  3. Video: Bioinformatics in Mainland China
  4. Video: About This Course
  5. 阅读: Readings
  6. 阅读: 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 expand


  1. Video: Essential Concepts
  2. Video: Global Alignment by Dynamic Programming
  3. Video: From Global to Local
  4. Video: Alignment with Affine Gap Penalty and Calculation of Time Complexity of The Needleman-Wunsch Algorithm
  5. Video: Interview with M. S. Waterman Waterman
  6. Video: Supplement on Homology & Similarity, Similarity Matrix and Dot Matrix (English Subtitles)
  7. Video: Student Presentation (English Subtitles)
  8. 阅读: Readings
  9. 阅读: 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 expand


  1. Video: Sequence Databases
  2. Video: BLAST Algorithm: A Primer
  3. Video: Student Presentation (English Subtitles)
  4. 阅读: Readings
  5. 阅读: 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 expand


  1. Video: From States to Markov Chain
  2. Video: Hidden Markov Model
  3. Video: Predict with Hidden Markov Model
  4. Video: Student Presentation
  5. 阅读: Readings
  6. 阅读: 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 expand


  1. Video: From Sequencing to NGS
  2. Video: Reads Mapping and Variants Calling
  3. Video: Computer Lab: Reads mapping and variant calling (English Subtitles)
  4. Video: Supplement on reads mapping and variant calling (English Subtitles)
  5. Video: Supplement on genotyping (English Subtitles)
  6. Video: A quick tour to sequencer 1 - Ion Torrent PGM (English Subtitles)
  7. Video: A quick tour to sequencer 2 - 3730 Sanger sequencing (English Subtitles)
  8. Video: Student presentation (English Subtitles)
  9. 阅读: Readings
  10. 阅读: 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 expand


  1. Video: Overview of the Problem
  2. Video: Variant Databases
  3. Video: Conservation-Based and Rule-Based Methods: SIFT & PolyPhen
  4. Video: Classifier-Based Methods: SAPRED
  5. Video: Introduction to Support Vector Machine(SVM) (English Subtitles)
  6. Video: Student presentation (English Subtitles)
  7. 阅读: Readings
  8. 阅读: 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 expand


    1. Video: Transcriptome: An Overview
    2. Video: RNA-Seq: Mapping & Assembling
    3. Video: Computer Lab: RNA-seq Data Analysis RNA-seq (English Subtitles)
    4. Video: Dr. Maynard Olson Talk
    5. Video: Student presentation (English Subtitles)
    6. 阅读: Readings
    7. 阅读: 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 expand


    1. Video: From Information to Knowledge
    2. Video: Data Mining: Identify long ncRNAs
    3. Video: Data Mining: Differential Expression and Clustering
    4. Video: Feature selection and Clustering (English Subtitles)
    5. Video: A quick tour to sequencer - illumina HiSeq & MiSeq (English Subtitles)
    6. Video: Student Presentation (English Subtitles)
    7. 阅读: Readings
    8. 阅读: 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 expand


    1. Video: Ontology and Gene Ontology
    2. Video: KEGG Pathway Database
    3. Video: Annotations in Gene Ontology
    4. Video: Pathway Identification
    5. Video: An Application: Common Molecular Pathways Underlying Addiction
    6. Video: Brief Introduction to Database (English Subtitles)
    7. Video: KOBAS Demo (English Subtitles)
    8. Video: Student presentation on KOBAS (English Subtitles)
    9. 阅读: Readings
    10. 阅读: 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 expand


    1. Video: Overview of Resources
    2. Video: National Center for Biotechnology Information
    3. Video: European Bioinformatics Institute
    4. Video: UCSC Genome Browser
    5. Video: Individual Resources
    6. Video: CBI Resources Review (English Subtitles)
    7. 阅读: 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 expand


    1. Video: New Gene Evolution Detected by Genomic Computation: Basic Concepts and Examples
    2. Video: New Gene Evolution Detected by Genomic Computation: A Driver for Human Brain Evolution
    3. Video: A Human-Specific de novo Gene Associated with Addiction
    4. Video: Origination of de novo Genes from Noncoding RNAs
    5. Video: Student Presentation (English Subtitles)
    6. 阅读: Readings
    7. 阅读: 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 expand


    1. Video: From Dry to Wet, an Evolutionary Story Part 1
    2. Video: Project background introduction by Dr. Gang Pei
    3. Video: From Dry to Wet, an Evolutionary Story Part 2
    4. Video: Talk with Dr. Gang Pei (English Subtitles)
    5. Video: Student Presentation (English Subtitles)
    6. 阅读: Slides


    WEEK 14


    Final Exam
    The description goes here




      Graded: Final Exam

      Werden Sie über neue Bewertungen benachrichtigt

      Es wurden noch keine Bewertungen geschrieben.

      Schreiben Sie eine Bewertung

      Haben Sie Erfahrung mit diesem Kurs? Schreiben Sie jetzt eine Bewertung und helfen Sie Anderen dabei die richtige Weiterbildung zu wählen. Als Dankeschön spenden wir € 1,00 an Stiftung Edukans.

      Es wurden noch keine FAQ hinterlegt. Falls Sie Fragen haben oder Unterstützung benötigen, kontaktieren Sie unseren Kundenservice. Wir helfen gerne weiter!

      Bitte füllen Sie das Formular so vollständig wie möglich aus

      (optional)
      (optional)
      (optional)
      (optional)

      Haben Sie noch Fragen?

      (optional)

      Anmeldung für Newsletter

      Damit Ihnen per E-Mail oder Telefon weitergeholfen werden kann, speichern wir Ihre Daten.
      Mehr Informationen dazu finden Sie in unseren Datenschutzbestimmungen.