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Tags: Reference material

All Categories (121-140 of 386)

  1. T2R38 taste receptor polymorphisms underlie susceptibility to upper respiratory infection

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Robert J Lee1, Guoxiang Xiong1, Jennifer M. Kofonow1

    University of Pennsylvania

    Article presenting evidence that the bitter taste receptor T2R38 regulates the mucosal innate defense of the human upper airway.

    https://qubeshub.org/qubesresources/publications/846/?v=1

  2. Sting, Carry and Stock: How Corpse Availability Can Regulate De-Centralized Task Allocation in a Ponerine Ant Colony

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Istvan Karsai1, Thomas Schmickl1

    East Tennessee State University

    Model showing that organization of work through a common stomach system can allow Ectatomma ruidum to collectively forage for food in a robust, reactive and reliable way

    https://qubeshub.org/qubesresources/publications/844/?v=1

  3. Web Popgen

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Bob Sheehy

    Radford University

    A Hardy-Weinberg simulation program.

    https://qubeshub.org/qubesresources/publications/842/?v=1

  4. Data Analysis for the Life Sciences

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Rafael A Irizarry1, Michael I Love1

    Harvard University

    An online stats book written completely in R

    https://qubeshub.org/qubesresources/publications/841/?v=1

  5. R Reference Card

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Tom Short

    EPRI PEAC

    Summary of reference info for using R

    https://qubeshub.org/qubesresources/publications/840/?v=1

  6. Rstudio cheatsheets

    22 Oct 2018 | Teaching Materials

    Cheatsheets are quickstart guides to using some of the most popular packages and features of Rstudio.

    https://qubeshub.org/qubesresources/publications/839/?v=1

  7. A Quick Guide to Teaching R Programming to Computational Biology Students

    22 Oct 2018 | Teaching Materials | Contributor(s):

    By Stephen Elgen

    University of Cambridge

    An introduction from an experienced educator in teaching R to computational biology graduate students.

    https://qubeshub.org/qubesresources/publications/838/?v=1

  8. A Very Basic Tutorial for Performing Linear Mixed Effects Analyses: Tutorial 2

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Bodo Winter

    University of California, Merced

    The second of two tutorials that introduce you to linear and linear mixed models. This tutorial serves as a quick boot camp to jump-start your own analyses with linear mixed effects models.

    https://qubeshub.org/qubesresources/publications/833/?v=1

  9. Linear Models and Linear Mixed Effects in R: Tutorial 1

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Bodo Winter

    University of California, Merced

    The first of two tutorials that introduce you to linear and linear mixed models.

    https://qubeshub.org/qubesresources/publications/832/?v=1

  10. Taking a Second Look: Investigating Biology with Visual Datasets

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Ethel Stanley

    Beloit College

    An article exploring the use of visual datasets as an educational aid for biology students.

    https://qubeshub.org/qubesresources/publications/831/?v=1

  11. Introductory Science and Mathematics Education for 21st-Century Biologists

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By William Bialek1, David Botstein2

    1. Department of Physics, Princeton University, Princeton, NJ 08544, USA., Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA. 2. Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA., Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.

    A unified introductory science curriculum that fully incorporates mathematics and quantitative thinking aimed to incorporate biology into the traditional quantitative cultures that have come to...

    https://qubeshub.org/qubesresources/publications/830/?v=1

  12. Towards better modelling and decision support: Documenting model development, testing, and analysis using TRACE

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Jacqueline Augusiak1, Andreas Focks1, Béatrice M. Frank2, Faten Gabsi3, Alice S.A. Johnston4, Chun Liu4, Benjamin T. Martin5, Mattia Meli6, Viktoriia Radchuk2, Pernille Thorbek7, Steven F Railsback8, Volker Grimm9

    1. Wageningen University, Aquatic Ecology and Water Quality Management Group, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands 2. Université Catholique de Louvain, Earth and Life Institute, Croix du Sud 2, 1348 Louvain-la-Neuve, Belgium 3. RWTH Aachen University, Institute for Environmental Research, Worringerweg 1, 52074 Aachen, Germany 4. University of Reading, School of Biological Sciences, Philip Lyle Building, Room 405, Reading RG6 6AS, UK 5. University of California Santa Barbara, Department of Ecology, Evolution, and Marine Biology, Santa Barbara, CA 93106-9620, USA 6. Roskilde University, Department of Environmental, Social and Spatial Change, Universitetsvej 1, P.O. Box 260, 4000 Roskilde, Denmark 7. yngenta, Environmental Safety, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, UK 8. Lang Railsback & Associates 9. Unknown

    We introduce TRACE, a framework for documenting model testing and analysis. TRACE is based on the recently proposed framework of model "evaluation" , and is designed to make models fit for...

    https://qubeshub.org/qubesresources/publications/829/?v=1

  13. How the Scientific Method Works

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Charles Bryant

    www.stuffyoushouldknow.com

    An episode dedicated to learning about how we explore our world using the scientific method.

    https://qubeshub.org/qubesresources/publications/827/?v=1

  14. Advancing population ecology with integral projection models: a practical guide

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Cory Merow1, Johan Dahlgren2, Jessica Metcalf3, Dylan Childs4, Margaret Evans5, Eelke Jongejans6, Sydne Record7, Mark Rees4, Roberto Salguero-Gómez8, Sean McMahon9

    1. Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA 2. Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden 3. Department of Zoology, Oxford University, Oxford, UK 4. Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK 5. Laboratory of Tree-Ring Research and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA 6. Department of Animal Ecology and Ecophysiology, Institute for Water and Wetland Research, Radboud University Nijmegen, Nijmegen, The Netherlands 7. Harvard University, Harvard Forest, Petersham, MA, USA 8. Centre for Biodiversity and Conservation Science, University of Queensland, St Lucia, Qld, Australia 9. Smithsonian Environmental Research Center, Edgewater, MD, Edgewater, MD, USA

    Integral projection models (IPMs) use information on how an individual's state influences its vital rates – survival, growth and reproduction – to make population projections using regression...

    https://qubeshub.org/qubesresources/publications/824/?v=1

  15. BioNumbers-the database of key numbers in molecular and cell biology

    19 Oct 2018 | Teaching Materials | Contributor(s):

    By Ron Milo1, Paul Jorgensen2, Michael Springer3

    1. Weizmann Institute of Science 2. Harvard Medical School 3. Beth Israel Deaconess Medical Center

    BioNumbers is a database of key numbers in molecular and cell biology—the quantitative properties of biological systems of interest to computational, systems and molecular cell biologists

    https://qubeshub.org/qubesresources/publications/821/?v=1

  16. Cell Biology by the Numbers

    18 Oct 2018 | Teaching Materials | Contributor(s):

    By Ron Milo1, Rob Phillips2

    1. Weizmann Institute of Science 2. California Institute of Technology

    Vignettes that reveal how numbers serve as a sixth sense to understanding our cells

    https://qubeshub.org/qubesresources/publications/819/?v=1

  17. R for biologists

    18 Oct 2018 | Teaching Materials | Contributor(s):

    By Marco Martinez

    University of Tennessee - Knoxville

    An introductory guide to data analysis in R for life sciences researchers.

    https://qubeshub.org/qubesresources/publications/815/?v=1

  18. BioNumbers: The Database of Useful Biological Numbers

    17 Oct 2018 | Teaching Materials | Contributor(s):

    By Ron Milo1, Paul Jorgensen2, Michael Springer2

    1. Weizmann Institute of Science 2. Harvard Medical School

    A database of biological numbers that you can search and browse.

    https://qubeshub.org/qubesresources/publications/813/?v=1

  19. Documenting teaching scholarship among undergraduate biology educators using OER

    11 Oct 2018 | Teaching Materials | Contributor(s):

    By Ahrash Bissell1, Lauren Collister2, Sam S Donovan2, Drew LaMar3, Hayley Orndorf2

    1. The Monterey Institute for Technology and Education 2. University of Pittsburgh 3. College of William and Mary

    Poster on the use, adaptation, and reuse of Open Educational Resources within the QUBES community at OpenEd 2018

    https://qubeshub.org/qubesresources/publications/734/?v=2

  20. Use of Peerwise and Twitter in Open Pedagogy

    10 Oct 2018 | Teaching Materials | Contributor(s):

    By Sarah Prescott

    University of New Hampshire

    This presentation will demonstrate the use of two open tools (Peerwise and Twitter) to engage students in creating and discussing course content.

    https://qubeshub.org/qubesresources/publications/804/?v=1