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You are here: Home / Tags / C5. Data retrieval / Teaching Materials

Tags: C5. Data retrieval

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C5. Find, retrieve, and organize various types of biological data. Given the numerous and varied datasets currently being generated from all of the ‘omics fields, students should develop the facility to: identify appropriate data repositories; navigate and retrieve data from these databases; and organize data relevant to their area of study in flat files or small local stand-alone databases.

  • Navigate and retrieve data from genome browsers
  • Retrieve data from protein and genome databases (e.g., PDB, UniProt, NCBI)
  • Store and interrogate small datasets using spreadsheets or delimited text files.

Teaching Materials (21-33 of 33)

  1. 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

  2. BSL-4: Authorized Personnel Only

    24 Sep 2018 | Teaching Materials | Contributor(s):

    By Nicole Anthony

    Biological Sciences, Toronto District School Board

    National Center for Case Study Teaching in Science resource on the 2014 Ebola epidemic. This resource is also included in the NIBLSE Learning Resource Collection

    https://qubeshub.org/publications/795/?v=1

  3. 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

  4. RNAseq data analysis using Galaxy

    13 Nov 2017 | Teaching Materials | Contributor(s):

    By Matthew Escobar1, Sam S Donovan2, Irina Makarevitch3, Bill Morgan4, Sabrina Robertson5

    1. California State University San Marcos 2. University of Pittsburgh 3. Hamline University 4. The College of Wooster 5. North Carolina State University

    This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.

    https://qubeshub.org/publications/118/?v=3

  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. RNAseq data analysis using Galaxy

    01 Aug 2017 | Teaching Materials | Contributor(s):

    By Matthew Escobar

    California State University - San Marcos

    This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.

    https://qubeshub.org/publications/118/?v=2

  8. Bioinformatics - Investigating Sequence Similarity

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

    By Adam Kleinschmit1, Benita Brink1, Steven Roof2, Komal Vig3, Carlos Christopher Goller4, Sabrina Robertson5

    1. Adams State University 2. Hampshire College 3. Alabama State University 4. North Carolina State University 5. NC State

    This laboratory module, leads introductory biology students in the exploration of a basic set of bioinformatics concepts and tools.

    https://qubeshub.org/publications/56/?v=3

  9. RNAseq data analysis using Galaxy

    03 Jul 2017 | Teaching Materials | Contributor(s):

    By Matthew Escobar

    California State University - San Marcos

    This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.

    https://qubeshub.org/publications/118/?v=1

  10. Bioinformatics - Investigating Sequence Similarity

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

    By Adam Kleinschmit1, Benita Brink1, Steven Roof2, Komal Vig3

    1. Adams State University 2. Hampshire College 3. Alabama State University

    This laboratory module, leads introductory biology students in the exploration of a basic set of bioinformatics concepts and tools.

    https://qubeshub.org/publications/56/?v=2

  11. 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

  12. Bioinformatics - Investigating Sequence Similarity

    31 Jan 2017 | Teaching Materials | Contributor(s):

    By Adam Kleinschmit1, Benita Brink1, Steven Roof2, Komal Vig3

    1. Adams State University 2. Hampshire College 3. Alabama State University

    This laboratory module, leads introductory biology students in the exploration of a basic set of bioinformatics concepts and tools.

    https://qubeshub.org/publications/56/?v=1

  13. 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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