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    A Critical Guide to Unix
    This Critical Guide in the Introduction to Bioinformatics series briefly introduces the Unix Operating System, and provides a subset of some of the most helpful and commonly used commands....
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    Integration of Bioinformatics into Life Science Curricula: Community Development, Dissemination, and Assessment of a NIBLSE Learning Resource
    Big data and computational tools have transformed the way we address biological questions. To prepare undergraduates for tomorrow’s challenges, life science curricula should integrate the...
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    Exploring the evolution of caffeine biosynthesis enzymes
    Caffeine is a very common stimulant consume worldwide as tea, coffee, mate, cocoa, and chocolate. Ever wondered why plants make caffeine? Do all caffeine producing plants have the same enzymes for...
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    Introduction to Genome Annotation
    This exercise is an adaptation of the Annotation Lesson by Rosenwald et al. It introduces the use of bioinformatics tools to extract information from genome databases. It is a basic lesson on...
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    Lesson I - Introduction to Genome Solver
    Genome Solver began as a way to teach undergraduate faculty some basic skills in bioinformatics; no coding or scripting is required. Part I is the Introduction to the Genome Solver Project.
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    Exploring HIV Evolution
    In this activity you will study aspects of sequence evolution by working with a set of HIV sequence data from 15 different subjects (Markham, et al., 1998). You will first learn about the dataset,...
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    Genome Solver - A bioinformatics pipeline for community science
    The Genome Solver was an NSF-funded project developed as a way to train undergraduate life science faculty in basic web-based tools for bioinformatics. As part of the project we developed a one-day...
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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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    Using Bioinformatics Activities to understand the Past and Present of SARS-CoV2
    We have designed a Bioinformatics activity that uses tools to identify the origins and mutations in the novel SARS-CoV2 strains.
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    Expanding Undergraduate Participation in Computational Biology: Resources and Lessons Learned from a Hands-on Workshop
    Presentation on computational biology in undergraduate education at the 2019 Great Lakes Bioinformatics Conference
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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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    Hidden Markov Model
    Hidden Markov models are a set of mathematical tools that can be used to draw inferences about genomic and evolutionary processes.
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    Deme 2.0
    This workbook simulates the population genetics of a single gene with two alleles. It can simultaneously model up to three local populations, which may differ in their selection coefficients.
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    Videos on Java for courses at University of Tennessee
    Eight videos developed by Hong Qin about using Java at the University of Tennessee Chattanooga
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    Java for-loop, investment problem, with debug flag usage demo
    BigJava Chapter 6, UTC CPSC1100 Fall 2017. Debug flag usage is shown.
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    ProteinPhysiochemistry
    How to determine physiochemical features of proteins using ExPasy Protpram, SOSUI server, and PSortB programs.
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    LEAGSEA
    How to perform Leading Edge Analysis in Gene Set Enrichment Analysis by Broad Institute
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    Using Phyre2
    How to use Phrye2 and 3DLigandSite to computationally predict protein and active site structure and binding partners (substrates/cofactors/coenzymes).
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    Simple Heat Maps with Morpheus
    Learn how to load an Excel file of raw data into Morpheus and change between relative and global scales.
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