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T-BioInfo in EducationT-BioInfo in Education
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    • Patient Derived Xenograft: Transcriptomic Biomarkers of Breast Cancer
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      • Introduction to Bioinformatics
      • Transcriptomics 1
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      • Metagenomics 1
      • More Courses
      • Specialization
      Metagenomics

      Metagenomics

      Free
      Read More
    • Specializations
      • Oncology
      • Immunology
      • Virology
      • Neurology
      • Agrotechnology
    • Events
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      • Patient Derived Xenograft: Transcriptomic Biomarkers of Breast Cancer
      • Analysis of Changing Immune Response in Cancer
      • Modeling Precision Medicine: Selecting Best Treatment Options For Patients Using “OMICS” Data
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    Transcriptomics 1

    From Raw Sequence to Gene Expression
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    • Omics Data Analysis
    • Transcriptomics 1

    Transcriptomics 1

    Claudia Copeland
    Claudia Copeland
    Omics Data Analysis, RNA-Seq
    (3 reviews)
    Free
    Transcriptomics 1
    • Description
    • Curriculum
    • Instructors
    • Review

    What is the transcriptome and why study it?

    Molecular biologists study a broad spectrum of topics relating to the molecular regulation of cell biology, from DNA and RNA, to protein expression and protein-protein interactions. A dominant theme in molecular biology is how variation in nucleic acids (genotype) affects the biology of organisms (phenotype). The second major theme is the study of gene expression and the resulting change in observed features of a studied sample.

    Next Generation Sequencing (NGS) is a key technology enabling an unprecedented level of precision and efficacy in understanding genomic and transcriptomic regulation. A Next Generation sequencer creates a digital file representing sequenced DNA or RNA. This file contains information where nucleotides are represented by letters corresponding to their “bases”. 

    Next Generation Sequencing data analysis is often referred to as “RNA-seq”. The purpose of this analysis is to map the short reads from raw sequence files to the reference genome and then study the abundance of RNA mapped to a particular region. The abundance can represent levels of gene or isoform expression and can be compared between samples or groups of samples.

    Course objectives and methodology

    The goal of this course is to prepare a student for real-world applications of RNA-seq. We will review methods of quantitative and qualitative analysis of RNA in a sample, how data is generated using Next Generation Sequencing and use a sample project “Patient Derived Xenograft: Transcriptomic Biomarkers of Breast Cancer” to practice generating a table of expression from raw FASTq files. We will also learn to preview and visualize the resulting data using Principal Component Analysis (PCA). To perform the example analysis detailed in the course, students will need access to the T-BioInfo platform. Account information can be requested in an email to info@pine-biotech.com. Microsoft Excel is also used for plotting results.

    We would like to thank the following people who helped to prepare the projects, develop the tools, and compile the the learning resources for this course:

    Dr. Leonid Brodsky and the Tauber Bioinformatics Research Center, Dr. Claudia Copeland, Dr. Ron Ferrucci, Julia Panov, Jaclyn Williams

    Course Features

    • Lectures 6
    • Quizzes 2
    • Duration 6 hours
    • Skill level All levels
    • Language English
    • Students 967
    • Certificate Yes
    • Assessments Self
    • Share:
    • From biological samples to RNA reads 0/4

      • Lecture1.1
        Biology of Transcription
        15 minute(s)
      • Lecture1.2
        Quantifying RNA: RNA-seq and other Techniques for RNA Analysis
        15 minute(s)
      • Lecture1.3
        Generating Transcriptome Expression Data
        15 minute(s)
      • Quiz1.1
        Transcriptomics 1 Quiz 1
        10 questions
    • From raw RNA-seq reads to expression table 0/3

      • Lecture2.1
        Logical steps for analyzing RNA-seq raw data
        18 minute(s)
      • Lecture2.2
        A Simple Example of RNA-seq Analysis
        11 minute(s)
      • Quiz2.1
        Transcriptomics 1 Quiz 2
        10 questions
    • Glossary 0/1

      • Lecture3.1
        Supplementary Resources
        30 minute(s)
    Claudia Copeland
    Claudia Copeland
    Dr. Copeland has a Ph.D. in molecular and cellular biology (Tulane University) and experience in both computational biology research and scientific writing, including educational writing in biology, chemistry, and bioinformatics. She enjoys teaching and communication of complex scientific topics to general audiences.

    Reviews

    Average Rating

    5
    3 ratings

    Detailed Rating

    5 stars
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    4 stars
    0
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    0
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    1 star
    0
    • khajapeer

      shaik

      its very good...i hope increase my knowledge

    • ahmadatallah

      Ahmad

      looks awesome and well organized materials

    • Description
    • Curriculum
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    • Review
    Free

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      7 Comments

    1. gottlieb.daphna
      September 11, 2017
      Log in to Reply

      where are all the lessons?

    2. tia25
      September 21, 2017
      Log in to Reply

      How do I enroll?

      • Ronald Ferrucci
        Ronald Ferrucci
        September 21, 2017
        Log in to Reply

        There should be an enrollment button, but it appears to be missing for some users and certain courses. We are working on getting to the bottom of this issue..

      • Ronald Ferrucci
        Ronald Ferrucci
        September 22, 2017
        Log in to Reply

        issue fixed, you should be able to enroll now

    3. ssethi
      October 17, 2017
      Log in to Reply

      This is simply awesome course. I loved this course. It made many of my concepts clear and the quiz was pretty exciting and challenging… looking forward to get enrolled in other courses too.

    4. Palak
      November 12, 2017
      Log in to Reply

      I recently took Transcriptomics 1 which helped me to clear my basics and gain an in-depth insight to what it is like to successfully handle data of any omics especially bioinformatics through excellent videos and quizzes. I look forward to utilizing the platform in research and gaining better knowledge of my core subjects.

    5. harryBRAR
      November 29, 2017
      Log in to Reply

      This is really helpful data … I am very thankful for this

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    All Courses

    Transcriptomics 3

    Transcriptomics 3

    Free
    Metagenomics

    Metagenomics

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    Genomics 1

    Genomics 1

    Free
    Transcriptomics 2

    Transcriptomics 2

    Free
    Transcriptomics 1

    Transcriptomics 1

    Free
    Introduction to Bioinformatics

    Introduction to Bioinformatics

    Free


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