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    Introduction to Quantitative Biology - Fall 2014 Syllabus
    Syllabus for Introduction to Quantitative Biology taught at the College of William and Mary.

    Keywords: quant biosyllabus

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

    Keywords: R

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    BIO 263 Ecological Data Analysis
    Course materials for BIO 263 Ecological Data Analysis
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    Plants by the Numbers
    Session presentation on quantitative botanical activities at the 2018 QUBES/BioQUEST Summer Workshop
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    AIMS- Analyzing Images to learn Mathematics and Statistics - studying leaf cutter ants to learn linear regression
    This is a teaching resource that uses fascinating images and videos of leaf cutter ants foraging in Panama to provide an engaging context for students to learn about mathematics and statistics.
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    Quantitative Reasoning Learning Progression
    Three articles about the work of a project on quantitative reasoning in the context of environmental literacy.

    Keywords: quantitative

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    Quantitative Modules to Accompany General Biology Courses
    A collection of modules that were developed to accompany general biology courses and allow instructors to add quantitative examples in many of the topics in a standard GB sequence.
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    Robot vs. Disease: Using CellProfiler to model biomedical research in your classroom
    Resource from the 2015 BioQUEST Summer Workshop
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    2015 Quantitative Biology Education Summit
    Abstract for a meeting, 2015 Quantitative Biology Education Summit.
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    CYTOSKELETON - Microtubule Dynamics in the Cell Cycle
    This module contains exercises designed to help upper-level cell biology students understand the dynamics of microtubule polymerization and depolymerization within the cell cycle and how cancer...
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    5-024-PhGreatLakes
    In this teaching modeling scenario, we demonstrate how lessons on salt-tank compartmental modeling can be used to predict phosphorus levels in the Great Lakes.
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    1-003-CollegeSavings-ModelingScenario
    We present a modeling opportunity for students in which they have to plan and model for saving for a child's complete college education.
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    EREN PFPP Species Composition Curriculum Module with Data
    In this lab, students will learn foundational concepts of forest community dynamics and apply quantitative skills to data analysis and interpretation activities. Students will use tree plot data...
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    2015-Heiko_Enderling-Integrating experimental data to calibrate quantitative cancer models
    For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer...
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    Bioinformatics / Neuroinformatics
    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...
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    Assessing River Herring Migration Using Nonparametric Analysis
    In this lesson, users will play the role of a fisheries biologist by tackling a contemporary fisheries research problem by performing data normality tests, data transformations, nonparametric...
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    QUBES: Building a community to promote undergraduate quantitative biology education
    This was a poster session at the 2015 Ecological Society of America meeting in Baltimore, MD.
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    Exercise on "Globally endangered sea turtles of the Palmyra Atoll National Wildlife Refuge: A Focus on Scientific Analysis"
    This data-driven endangered sea turtle exercise adapted from http://qubeshub.org was developed for undergraduate students in an online non-majors biology course as a final small group project.

    Keywords: Resource Type

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    5-036-HalfCarVibration-ModelingScenario
    Vibration vehicle models provide an opportunity to integrate vehicle-based vibrations into a mechanical engineering vibrations course. The project is on a multiple-degree-of-freedom (MDOF)...
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    1-024-MalariaControl-ModelingScenario
    This project offers students a chance to make policy recommendations based on the analysis of models using both linear (exponential decay) and non-linear (logistic growth) differential equations.
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