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C4. Use bioinformatics tools to examine complex biological problems in evolution, information flow, and other important areas of biology. This competency is written broadly so as to encompass a variety of problems that can be addressed using bioinformatics tools, such as understanding the evolutionary underpinnings of sequence comparison and homology detection; distinguishing between genomic sequences, RNA sequences, and protein sequences; and 
23 interpreting phylogenetic trees. “Complex” biological problems require that students should be able to work through a problem with multiple steps, not just perform isolated tasks. 

  • Using multiple lines of evidence, annotate a gene.
  • Develop and interpret a “tree of life” based on a BLAST search, multiple alignment, and
    phylogenetic-tree building.
  • Explain how a mutation in a gene causes cancer, using a genome browser to identify the gene, transcript, and affected protein, and tools such as OMIM, GO, and KEGG to place it in the context of a function and pathway important to the disease.

Teaching Materials (1-10 of 10)

  1. Genome Solver: Complete Set of Lessons

    23 Oct 2019 | Teaching Materials | Contributor(s):

    By Anne Rosenwald1, Gaurav Arora2, Vinayak Mathur3

    1. Georgetown University 2. Gallaudet University 3. Cabrini University

    The Genome Solver Project began as a way to teach faculty some basic skills in bioinformatics - no coding or scripting. These Lessons also work well in the undergraduate classroom, culminating with...

    https://qubeshub.org/publications/860/?v=2

  2. Using Synthetic Biology to Teach Data Science

    26 Jun 2019 | Teaching Materials | Contributor(s):

    By Margaret S Saha1, Beteel Abu-Ageel1, Sanjana Challa1, Xiangyi Fang1, Chai Hibbert1, Anna Isler1, Elias Nafziger1, Adam Oliver1, Hanqiu Peng1, Julia Urban1, Vivian Zhu1

    College of William and Mary

    Abstract for poster on using synthetic biology to introduce students to meaningful data mining, analysis, and application to engineering novel biological constructs.

    https://qubeshub.org/publications/1326/?v=1

  3. Complete Set of Lessons

    01 Nov 2018 | Teaching Materials | Contributor(s):

    By Anne Rosenwald1, Gaurav Arora2, Vinayak Mathur3

    1. Georgetown University 2. Gallaudet University 3. Cabrini University

    The Genome Solver Project began as a way to teach faculty some basic skills in bioinformatics - no coding or scripting. These Lessons also work well in the undergraduate classroom, culminating with...

    https://qubeshub.org/publications/860/?v=1

  4. Using DNA Subway to Analyze Sequence Relationships

    28 May 2018 | Teaching Materials | Contributor(s):

    By Jason Williams1, Ray A. Enke2, Oliver Hyman2, Emily Lescak3, Sam S Donovan4, William Tapprich5, Elizabeth F Ryder6

    1. DNA Learning Center 2. The Department of Biology, James Madison University; The Center for Genome & Metagenome Studies, James Madison University 3. University of Alaska 4. University of Pittsburgh 5. University of Nebraska-Omaha 6. Worcester Polytechnic Institute

    This is a bioinformatics exercise using the DNA Subway Blue Line, a user-friendly pipeline of bioinformatics tools, to analyze a collection of mosquito DNA bar-code sequences.

    https://qubeshub.org/publications/165/?v=2

  5. DNA Subway Learning Resources

    18 Oct 2017 | Teaching Materials | Contributor(s):

    By Jason Williams

    DNA Learning Center

    DNA Subway is a NIBLSE Recommended resource. This is a collection of learning resources associated with DNA Subway.

    https://qubeshub.org/publications/164/?v=2

  6. Using DNA Subway to Analyze Sequence Relationships

    18 Oct 2017 | Teaching Materials | Contributor(s):

    By Jason Williams

    DNA Learning Center

    This is a bioinformatics exercise using DNA Subway

    https://qubeshub.org/publications/165/?v=1

  7. Exploring HIV Evolution

    05 Jun 2017 | Teaching Materials | Contributor(s):

    By Sam S Donovan1, Tony Weisstein2

    1. University of Pittsburgh 2. Truman State University

    In this activity you will study aspects of sequence evolution by working with a set of HIV sequence data from 15 different subjects (Markham, et al., 1998). You will first learn about the dataset,...

    https://qubeshub.org/publications/24/?v=2

  8. RNA-seq Analysis

    05 Jun 2017 | Teaching Materials | Contributor(s):

    By Bill Morgan1, Matthew Reeder2

    1. The College of Wooster 2. Ohio State University

    In this computer lab module, students learn how to process an RNA-seq data set to identify differentially expressed genes (DEGs). The samples for this data set were collected from yeast cells...

    https://qubeshub.org/publications/27/?v=2

  9. Exploring HIV Evolution

    05 Aug 2016 | Teaching Materials | Contributor(s):

    By Sam S Donovan1, Tony Weisstein2

    1. University of Pittsburgh 2. Truman State University

    In this activity you will study aspects of sequence evolution by working with a set of HIV sequence data from 15 different subjects (Markham, et al., 1998). You will first learn about the dataset,...

    https://qubeshub.org/publications/24/?v=1

  10. RNA-seq Analysis

    03 Aug 2016 | Teaching Materials | Contributor(s):

    By Bill Morgan1, Matthew Reeder2

    1. The College of Wooster 2. Ohio State University

    In this computer lab module, students learn how to process an RNA-seq data set to identify differentially expressed genes (DEGs). The samples for this data set were collected from yeast cells...

    https://qubeshub.org/publications/27/?v=1

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