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

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Página inicialCiências BiológicasBioinformática

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

Universidade de PequimUniversidade de Pequim

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.


Desenvolvido por:  Universidade de PequimUniversidade de Pequim
Universidade de PequimUniversidade de Pequim

  • Ge Gao 高歌, Ph.D.

    Ministrado por:  Ge Gao 高歌, Ph.D., Assistant Professor, Principle Investigator

    Center for Bioinformatics, School of Life Science

  • Liping Wei 魏丽萍, Ph.D.

    Ministrado por:  Liping Wei 魏丽萍, Ph.D., Professor, Director

    Center for Bioinformatics, School of Life Sciences
Compromisso1-2 hours/week
Idioma
English
Como ser aprovadoSeja aprovado em todas as tarefas para concluir o curso.
Classificação do usuário
4.7 estrelas
Classificação média do usuário 4.7Veja o que os aprendizes disseram
Programa
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: What is Bioinformatics
  2. Vídeo: History of Bioinformatics
  3. Vídeo: Bioinformatics in Mainland China
  4. Vídeo: About This Course
  5. Reading: Readings
  6. Reading: Slides
Nota atribuída: Introduction and History of Bioinformatics
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: Essential Concepts
  2. Vídeo: Global Alignment by Dynamic Programming
  3. Vídeo: From Global to Local
  4. Vídeo: Alignment with Affine Gap Penalty and Calculation of Time Complexity of The Needleman-Wunsch Algorithm
  5. Vídeo: Interview with M. S. Waterman Waterman
  6. Vídeo: Supplement on Homology & Similarity, Similarity Matrix and Dot Matrix (English Subtitles)
  7. Vídeo: Student Presentation (English Subtitles)
  8. Reading: Readings
  9. Reading: Slides
Nota atribuída: Sequence Alignment
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: Sequence Databases
  2. Vídeo: BLAST Algorithm: A Primer
  3. Vídeo: Student Presentation (English Subtitles)
  4. Reading: Readings
  5. Reading: Slides
Nota atribuída: Sequence Database Search
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: From States to Markov Chain
  2. Vídeo: Hidden Markov Model
  3. Vídeo: Predict with Hidden Markov Model
  4. Vídeo: Student Presentation
  5. Reading: Readings
  6. Reading: Slides
Nota atribuída: Markov Model
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: From Sequencing to NGS
  2. Vídeo: Reads Mapping and Variants Calling
  3. Vídeo: Computer Lab: Reads mapping and variant calling (English Subtitles)
  4. Vídeo: Supplement on reads mapping and variant calling (English Subtitles)
  5. Vídeo: Supplement on genotyping (English Subtitles)
  6. Vídeo: A quick tour to sequencer 1 - Ion Torrent PGM (English Subtitles)
  7. Vídeo: A quick tour to sequencer 2 - 3730 Sanger sequencing (English Subtitles)
  8. Vídeo: Student presentation (English Subtitles)
  9. Reading: Readings
  10. Reading: Slides
Nota atribuída: Next Generation Sequencing (NGS)
SEMANA 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 vídeos, 2 leituras
  1. Vídeo: Overview of the Problem
  2. Vídeo: Variant Databases
  3. Vídeo: Conservation-Based and Rule-Based Methods: SIFT & PolyPhen
  4. Vídeo: Classifier-Based Methods: SAPRED
  5. Vídeo: Introduction to Support Vector Machine(SVM) (English Subtitles)
  6. Vídeo: Student presentation (English Subtitles)
  7. Reading: Readings
  8. Reading: Slides
Nota atribuída: Functional Prediction of Genetic Variants
SEMANA 7
Mid-term Exam
The description goes here
    Nota atribuída: Mid-term Review
    SEMANA 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 vídeos, 2 leituras
    1. Vídeo: Transcriptome: An Overview
    2. Vídeo: RNA-Seq: Mapping & Assembling
    3. Vídeo: Computer Lab: RNA-seq Data Analysis RNA-seq (English Subtitles)
    4. Vídeo: Dr. Maynard Olson Talk
    5. Vídeo: Student presentation (English Subtitles)
    6. Reading: Readings
    7. Reading: Slides
    Nota atribuída: Next Generation Sequencing: Transcriptome Analysis, and RNA-Seq
    SEMANA 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 vídeos, 2 leituras
    1. Vídeo: From Information to Knowledge
    2. Vídeo: Data Mining: Identify long ncRNAs
    3. Vídeo: Data Mining: Differential Expression and Clustering
    4. Vídeo: Feature selection and Clustering (English Subtitles)
    5. Vídeo: A quick tour to sequencer - illumina HiSeq & MiSeq (English Subtitles)
    6. Vídeo: Student Presentation (English Subtitles)
    7. Reading: Readings
    8. Reading: Slides
    Nota atribuída: Prediction and Analysis of Noncoding RNA
    SEMANA 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 vídeos, 2 leituras
    1. Vídeo: Ontology and Gene Ontology
    2. Vídeo: KEGG Pathway Database
    3. Vídeo: Annotations in Gene Ontology
    4. Vídeo: Pathway Identification
    5. Vídeo: An Application: Common Molecular Pathways Underlying Addiction
    6. Vídeo: Brief Introduction to Database (English Subtitles)
    7. Vídeo: KOBAS Demo (English Subtitles)
    8. Vídeo: Student presentation on KOBAS (English Subtitles)
    9. Reading: Readings
    10. Reading: Slides
    Nota atribuída: Ontology and Identification of Molecular Pathways
    SEMANA 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 vídeos, 1 leitura
    1. Vídeo: Overview of Resources
    2. Vídeo: National Center for Biotechnology Information
    3. Vídeo: European Bioinformatics Institute
    4. Vídeo: UCSC Genome Browser
    5. Vídeo: Individual Resources
    6. Vídeo: CBI Resources Review (English Subtitles)
    7. Reading: Slides
    Nota atribuída: Bioinformatics Database and Software Resources
    SEMANA 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 vídeos, 2 leituras
    1. Vídeo: New Gene Evolution Detected by Genomic Computation: Basic Concepts and Examples
    2. Vídeo: New Gene Evolution Detected by Genomic Computation: A Driver for Human Brain Evolution
    3. Vídeo: A Human-Specific de novo Gene Associated with Addiction
    4. Vídeo: Origination of de novo Genes from Noncoding RNAs
    5. Vídeo: Student Presentation (English Subtitles)
    6. Reading: Readings
    7. Reading: Slides
    Nota atribuída: Origination of New Genes
    SEMANA 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 vídeos, 1 leitura
    1. Vídeo: From Dry to Wet, an Evolutionary Story Part 1
    2. Vídeo: Project background introduction by Dr. Gang Pei
    3. Vídeo: From Dry to Wet, an Evolutionary Story Part 2
    4. Vídeo: Talk with Dr. Gang Pei (English Subtitles)
    5. Vídeo: Student Presentation (English Subtitles)
    6. Reading: Slides
    SEMANA 14
    Final Exam
    The description goes here
      Nota atribuída: Final Exam

      Perguntas frequentes
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      Universidade de PequimUniversidade de Pequim
      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.
      Classificações e avaliações
      Avaliado em 4.7 de 5 decorrente de 93 avaliações
      王思雨

      GOOD

      ZT

      this is a good course from china

      Wenjie Xu

      课程很好,很多东西,对今后的研究工作恩达的帮助!

      shang lingling

      Great!



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