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    RNAseq data analysis using Galaxy
    This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.
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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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    Finding Selection in All the Right Places
    Lab introducing students to evolutionary genetics using bioinformatics and biocuration, published as GSA Learning Resource
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    Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching
    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...
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    The Stomata Lab. What the past can tell us about our future - using fossil and modern plants to model atmospheric carbon dioxide
    Students will develop a mathematical model of the relationship between atmospheric CO2 and the number of stomata on a leaf (Stomata Index). They will evaluate the model graphically, statistically,...
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    Using the Hardy-Weinberg Equations: Quantifying Natural Selection and Allele Frequencies
    This module contains exercises designed to walk students through a real-world example of the coevolution of fruit color and primate frugivore color vision. Students will apply the Hardy-Weinberg...
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    The Edge Effect
    This module has students venturing outdoors to take a 50m transect and collect abundance data on plants utilizing quadrats in both edge and interior environment. Mathematically the goals of this...
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    BIO 439/539: Big Data Analysis
    Course materials for BIO 439/539: Big Data Analysis
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    Statistics for Biologists
    There is no disputing the importance of statistical analysis in biological research, but too often it is considered only after an experiment is completed, when it may be too late.
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    An Introduction to Statistical Learning: with Applications in R
    This book provides an introduction to statistical learning methods and is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.
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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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    Statistical Exploration of Climate Data
    In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis.
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    Data Analysis for the Life Sciences
    An online stats book written completely in R
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    A Critical Guide to the PDB
    This Critical Guide in the Introduction to Bioinformatics series provides a brief outline of the Protein Data Bank – the PDB – the world’s primary repository of biological macromolecular structures.
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    A Critical Guide to BLAST
    This Critical Guide in the Introduction to Bioinformatics series provides an overview of the BLAST similarity search tool, briefly examining the underlying algorithm and its rise to popularity.
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    Infectious Chocolate Joy with a Side of Poissonian Statistics: An activity connecting life science students with subtle physics concepts
    Lesson on what it means for biological processes to be Poissonian, published in CourseSource
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    A Hands-on Introduction to Hidden Markov Models
    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.
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    Java Applets for Power and Sample Size
    This is a Java application that allows you to do power and sample-size calculations for a number of standard statistical models.
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    The Human Microbiome Biodiversity in Health and Disease
    The students will analyze the human gut and vaginal microbiomes in healthy and diseased states using diversity of bacteria as determined by 16SrRNA sequence.
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    Transpiration
    In this lab, students will examine differences between C3 and C4 plants in their transpiration rates.
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