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You are here: Home / Tags / C3. Statistical concepts / All Categories

Tags: C3. Statistical concepts

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C3. Apply statistical concepts used in bioinformatics. In addition to the basic statistics found in many biology curricula, modern life scientists should have an understanding of the statistics of large datasets and multiple comparisons. 

  • Understand that there is a probability of finding a given sequence similarity score by chance (the P value) and that the size of the target database affects the probability that you will see a particular score in a particular search (the E-value).
  • Explain the statistical modeling used to identify differentially expressed genes.
  • Interpret data from a well-designed drug trial.

All Categories (1-8 of 8)

  1. Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching

    04 Jan 2019 | Teaching Materials | Contributor(s):

    By Mark Phillip Peterson1, Jacob T Malloy2, Vincent P Buonaccorsi2, James H Marden3

    1. Viterbo University 2. Juniata College 3. Pennsylvania State University

    This lesson plan was created to teach RNAseq analysis as a part of GCAT-SEEK network. It is provided here, both in finished form and with the modifiable source code, to allow flexible adaptation to...

    https://qubeshub.org/qubesresources/publications/1005/?v=1

  2. Infectious Chocolate Joy with a Side of Poissonian Statistics: An activity connecting life science students with subtle physics concepts

    04 Jan 2019 | Teaching Materials | Contributor(s):

    By Eric T. Holland1, Greg Manley1, Tamara Chiba1, Rona Ramos1, Simon Mochrie1, Jennifer Frederick1

    Yale University

    Lesson on what it means for biological processes to be Poissonian, published in CourseSource

    https://qubeshub.org/qubesresources/publications/1001/?v=1

  3. A Hands-on Introduction to Hidden Markov Models

    04 Jan 2019 | Teaching Materials | Contributor(s):

    By Tony Weisstein1, Elena Gracheva2, Zane Goodwin2, Zongtai Qi2, Wilson Leung2, Christopher D. Shaffer2, Sarah C.R. Elgin2

    1. Truman State University 2. Washington University in St. Louis

    A lesson in which students will understand the basic structure of an HMM, the types of data used in ab initio gene prediction, and its consequent limitations.

    https://qubeshub.org/qubesresources/publications/999/?v=1

  4. Finding Selection in All the Right Places

    03 Jan 2019 | Teaching Materials | Contributor(s):

    By Juliet F. K. Noor, Mohamed A. F. Noor

    Lab introducing students to evolutionary genetics using bioinformatics and biocuration, published as GSA Learning Resource

    https://qubeshub.org/qubesresources/publications/994/?v=1

  5. Bioinformatics / Neuroinformatics

    03 Jan 2019 | Teaching Materials | Contributor(s):

    By William Grisham

    University of California, Los Angeles

    This module is a computer-based introduction to bioinformatics resources. This easy-to-adopt module weaves together several important bioinformatic tools so students can grasp how each is used in...

    https://qubeshub.org/qubesresources/publications/990/?v=1

  6. 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/qubesresources/publications/118/?v=3

  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/qubesresources/publications/118/?v=2

  8. 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/qubesresources/publications/118/?v=1

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