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Obtaining and Using Computer Based Tools for the Freshman and Sophomore Biology Laboratory. 12 th Annual Technology Conference October 6, 2006. Christopher Harendza, Professor of Biology. Abstract.

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Obtaining and using computer based tools for the freshman and sophomore biology laboratory

Obtaining and Using Computer Based Tools for the Freshman and Sophomore Biology Laboratory

12th Annual Technology Conference

October 6, 2006

Christopher Harendza, Professor of Biology


Abstract
Abstract and Sophomore Biology Laboratory

Biology has experienced an explosion of DNA sequence data and the human genome and those of several model organisms are complete. There are numerous free web based tools available to analyze this data. In addition, many laboratory exercises have been adapted to computer programs; some are traditional laboratories but many are mathematical models of complex processes that could not be studied in the lab. MCCC is in the third year of an NSF grant to implement the aforementioned approaches to the teaching of bioscience majors. The forum will discuss the grant process and current status of the project.


Today s discussion
Today’s Discussion and Sophomore Biology Laboratory

  • Project Goals

  • National Science Foundation – CCLI A&I Program

  • Examples of What is Being Done

  • A Critique

  • Future Plans


P r o j e c t g o a l
P R O J E C T G O A L and Sophomore Biology Laboratory

Traditional Science

Education Model

Inquiry &

Project

Based Labs

Curriculum

evolution

“Cook Book

Labs”


Curriculum change
Curriculum Change and Sophomore Biology Laboratory

  • Evolution vs. “reform”

  • Keep the best of the old and bring in a fresh approach

  • Maintain standards


http://www.nsf.gov/


Project Based Activities and Sophomore Biology Laboratory

Inquiry Based Labs

Data Analysis

Bioinformatics

Modeling

Collaboratories


Course curriculum laboratory improvement ccli areas of support
Course, Curriculum &Laboratory Improvement (CCLI) Areas of Support

Biological Sciences

Chemistry

Computer Science

Engineering

Geological Sciences

Interdisciplinary

Mathematics

Physics/Astronomy

Research/Assessment

Social Sciences


Goal of nsf ccli
Goal of NSF CCLI Support

  • “to promote excellent science, technology, engineering, and mathematics (STEM) education for all undergraduate students”


Ccli tracks
CCLI Tracks Support

  • Educational Materials Development (EMD)

  • Adaptation and Implementation (A&I)

  • National Dissemination (ND)

  • Assessment of Student Achievement (ASA)


Adaptation and implementation a i
Adaptation and Implementation (A&I) Support

  • Adapt and implement

    • find existing funded projects and modify (adapt) them to your situation

  • Carry out project

  • Disseminate what you have done to encourage change (“reform”)


A i areas
A&I areas Support

  • “incorporation of laboratory experiments or field experiences that engage students in scientific processes and exploration of scientific concepts”

  • “adaptation and testing of exemplary materials for use by a student population significantly different from the one for which they were originally developed”


A i areas con t
A&I Areas, con’t Support

  • “enhancement of teaching and learning through the use of resources, particularly instructional and information technologies, demonstrated to be of high quality”

  • “development and use of collaborative learning, learning communities, peer-led teaching, etc. that aim to improve pedagogy in courses”

  • “integration of significant advances or techniques from research fields into the undergraduate curriculum”


Finding ideas
Finding ideas: Support

  • Search awards for thing (s) you like

  • Get help from your grants office

  • Write proposal


Adapt implement
Adapt & Implement Support

past funded projects:

PCs for laboratory work

Grant:

Laptops for a

Combined lab/ lecture/discussion setting

computer modeling

of complex labs

bioinformatics


Nsf grant
NSF Grant Support


Specifics
Specifics Support

  • 13 student laptops with wireless internet connections

  • Wireless hub

  • Bioquest™, MicrobesCount™ & Virtual Fly software, etc.

  • Digital electrophoresis documentation system

  • Labor for IT and development


Bioquest packages
BioQUEST packages Support

  • BIRDD

  • DNA Electrophoresis

  • Fly a Cell

  • Lateblight

  • Metabolic Pathways

  • PEACH

  • Resistan

  • Winter Twig Key


Problems w bq
Problems w/ BQ Support

  • Many of the better modules, e.g. Genetics Construction Kit, are Mac only

  • Not updated – a bit unsophisticated

  • Some things too advanced for freshman biology

  • Sometimes not easy to use


Microbescount
MicrobesCount! Support

  • ASM / BQ venture

  • Newer, nicer

  • Good mathematical modeling


Some microbescount labs
Some MicrobesCount! Labs Support

  • The Scale of the Microbial World

  • Modeling Wine Fermentation **

  • Biosphere2: Unexpected Interactions **

  • Modeling Microbial Growth: TB and Antibiotic Resistance

  • Conjugation and Genetic Mapping

  • Tree of Life: Intro to Microbial Phylogeny **


Combined and adapted to protein explorer
Combined and adapted to Protein Explorer Support

  • Searching for Amylase

  • Proteins: Historians of Life on Earth

  • Visualizing Microbial Proteins

  • (see below)


Virtual fly
Virtual Fly Support

  • Flexible and powerful model for use in genetic crosses using the classic model Drosophila


Clustal applications
CLUSTAL Applications Support

  • Exploring HIV Evolution: An Opportunity for Research

  • Tree of Life: Introduction to Microbial Phylogeny

  • Tracking the West Nile Virus ***



Definitions of bioinformatics
Definitions of Bioinformatics Support

  • any use of computers to handle biological information

  • computational molecular biology

  • the use of computers to characterize the molecular components of living things



Biology workbench tools
Biology Workbench Tools Support

  • BLAST

    • Amino acid

    • Nucleic acid

  • CLUSTAL

    • Amino Acid

    • Nucleic Acid

Many variations

and special

applications


Some specific examples
Some Specific Examples Support

  • Protein Explorer

  • Winemox fermentation to model alcohol production in a winery

  • [email protected] ecosystem model

  • CLUSTAL W to study the spread of West Nile virus

  • BLAST to study orthology

  • Virtual fly


Protein explorer
Protein Explorer Support

  • Molecular visualization program

  • Allows study of proteins in 3 dimensions


Uses Support

Go to PE

You will need a plugin

called “chime”

  • Modeling of insulin (PDB code = 1APH)

    • Simple and important protein

    • Only 51 amino acids, DM

  • Hemoglobin (PDB code 1HGA; HbS/HbS PDB code = 2HbS)

    • Well studied

    • Common thread throughout course

    • Applications to sickle cell: evolution, multiculturalism, etc.


Pe outcome positives
PE Outcome: positives Support

  • Excellent Flash Tutorial on use

  • Better appreciation for protein structure

  • Student exposure to authentic research data and models for protein structure


Pe outcomes negatives
PE Outcomes: Negatives Support

  • Can be complicated for students who are ill prepared

  • Descriptive, not very experimental

  • Time consuming


Wine mox
Wine.mox Support

  • Mathematical model based on Extend software

  • Used as a “part II” to augment an existing wet lab on fermentation

    • Fermentation vs. time

    • Fermentation vs. time + O2 (Pasteur effect)

      • Both use MS Excel graphing




Use of wine mox
Use of Wine.mox Support

  • Students hypothesize on how to increase ethanol production

  • Increase glucose concentration

  • Increase stress factors of yeast (wild yeasts ferment <<< 12% alcohol)

  • Possible to make other models




Ecosystem modeling
Ecosystem modeling Support

  • Ecologists use mathematical models extensivley and field work is often not possible

Biosphere II, Tuscon, AZ


Simbio 2 model ran in lab went to blackboard wiki collaboratory
SimBio 2 Model: SupportRan in lab & went to Blackboard Wiki Collaboratory



Questions from the results above
Questions from the results above: Support

  • What is the relationship between CO­2 concentration and O2 concentration?

  • Why is there a cyclical fluctuation between CO2 and O2 concentration?


Next question
Next question Support

  • What is the maximum number of people Bio2 can support?

    • If O2 levels drop below 12% it seriously impairs human physiology


N = 16 Support


N = 32 Support


N 256
N=256 Support


Conclusion
Conclusion Support

  • 3 acres of land does not support very many people!

  • O2 levels still decline to dangerously low levels – Why?

    • It turns out it was the biomass and the ants using the O2 to decompose it!


Effect of the soil
Effect of the soil Support

  • Biosphere2 was built using soil that was with unusually heavy in organic matter; hence the soil had fairly high rates of respiration

  • What affect does simulating a sandy soil (with less organic material) have?


West nile virus migration
WEST NILE VIRUS MIGRATION Support

  • Use CLUSTAL site at Biology Workbench

    • multiple sequence alignment program: aligns sequences & depicts the differences

    • examines relatedness, based on mutation rate



Can do the same with hiv
Can do the same with HIV Support

>HIV Isolate 1

1 gaggtagtaa ttagatccat aaatttctca gacaatgcta aaatcataat agtacatcta

61 aatgaatctg tagaaattaa ttgtacaaga cccggcaaca atacaagaag aagtatacat

121 ataggaccaa acagagcatt ttatacaaca ggagacataa taggagatat aagacaagca

181 cattgtaaca ttagtgaaga aaaatggaat gaaaccttaa aaaagatagt tataaaatta

241 agagaacaat ttaagaataa aacaatagta tttaagtcat cctca

>HIV Isolate 2

1 gaggtagtaa ttagatctga aaatttcacg aacaatgcta aaatcataat agtacagctg

61 aatgaatctg tagaaattaa ttgtacaaga cccaacaaca atacaagaag aagtataaat

121 ataggaccag ggagagcatt ttatgcaaca ggagatataa taggagatat agggcaagca

181 cattgtaacc ttagtagagc aaaatggaat gacactttaa aacagatagt ttacaaatta

241 agagaacaat ttgggaataa taaaacaata atctttaatc aatcctca

>HIV Isolate 3

1 gatatagtaa ttagatctgc caatttctcg gacaatgcta aaaccatatt agtacagctg

61 aatgaaactg tagtaatgaa ttgtacaaga cccggcaaca atacaagaaa aagggtaact

121 ctaggaccag gcagagtata ctatacaaca ggacaaataa taggagatat aagaaaagca

181 cattgtaacc ttagtagagc ggattggaat aacactttag aaaggatagc tataaaatta

241 tgagaacaat ttcagaataa aacaataggc tttaatcaat cctca

>HIV Isolate 4

1 gaggtagtaa ttagatccgt caatctcacg gacaatgcta aagtcataat agtacatctg

61 aatgaatctg tagaaatgaa ttgtacaaga cccaacaaca atacaagaaa aaggatatct

121 ctaggaccag gcagagtata ttatacaaca ggagaaataa taggagatat aagaaaagca

181 tattgtaaca ttagtagagc aaaatggaat gatactttaa aaaatatagc tataaaatta

241 agagaacaat ttaagaataa aacaatagtc tttaagcaat cctca

>HIV Isolate 5

1 gaggtagtaa ttagatccgt caatctcacg gacaatgcta aagtcataat agtacatctg

61 aatgaatctg tagagatgaa ttgtacaaga cccaacaaca atacaagaaa aagtatatct

121 ataggaccag gcagagcatt ttatacaaca ggagaaataa taggagatat aagacaagca

181 cattgtaacc ttagtagagc aaaatggaat gacactttaa aaaatatagc tataaaatta

241 agagaacaat ttaagaataa aacaatagtc tttaatcaat cctca

>HIV Isolate 6

1 gaggtagtaa ttagatctga aaatttcacg aacaatgcta aaattataat agtacagctg

61 aatgaatctg tagaaattaa ttgtacaaga cccgacaaca atacagtaag aaagatacct

121 ataggaccag ggagttcatt ttatacaaca ggcagagtag gagatataag gcaagcacat

181 tgtaacatta gtagaacaaa atggaataac actttaaaac tgatagttaa caaattaaga

241 gaacaatttg ggaataaaac aataatcttt aatcaatcct ca

Go to BWB


Using blast
Using BLAST Support

  • = Basic Local Alignment Search Tool

  • Searches databases for orthologs and homologs (i.e. related genes or proteins)

  • BLAST-N and BLAST-P


Give student a dna sequence of unknown id but know phenotype e g cell division mutant
Give student a DNA sequence of unknown ID, but know phenotype, e.g. cell division mutant

Normal above

Abnormal left


Blast clustal
BLAST & CLUSTAL phenotype, e.g. cell division mutant

  • Plusses:

    • Real data, real science

    • Makes them really accept evolution!

  • Minuses:

    • Very difficult for some of the students

    • May try “geneious”


Virtual fly1
Virtual Fly phenotype, e.g. cell division mutant

  • Provides very flexible and powerful models for use in genetic crosses using the classic model Drosophila

  • http://biologylab.awlonline.com/


Uses of virtual fly
Uses of Virtual Fly phenotype, e.g. cell division mutant

  • Give students several mutant flies and they must design crosses to determine the inheritance pattern

    • wingless

    • Bar Eye

    • Yellow body

  • Advanced genetics

    • 3 point crosses, linkage and mapping

    • Crosses for epistasis, etc.


Virtual fly2
Virtual Fly phenotype, e.g. cell division mutant

  • Minuses:

    • Addison Wesley Web site

    • Not a substitute for the real thing

  • Positives:

    • Excellent way to teach genetics

    • Well established and tie to Flybase (see below)


Conclusions critique
Conclusions & Critique phenotype, e.g. cell division mutant

Traditional Science

Education Model

Inquiry &

Project

Based Labs

Curriculum

evolution

“Cook Book

Labs”


Project critique minuses first
Project Critique: minuses first phenotype, e.g. cell division mutant

  • Batting about << 500 with efficacy

  • Students can not handle much of what has been proposed

  • Sometimes time consuming: tradeoff of balancing content and new ideas

  • Alteration of plant has led to new ideas

  • Many of the models are BORING!


Critique positives
Critique: Positives phenotype, e.g. cell division mutant

  • Collaborative learning is a plus

    • Student group work in class

    • BlackBoard discussion and Wiki

  • Improvement of data analysis skills

  • Stimulating, exciting, new


New ideas
New Ideas phenotype, e.g. cell division mutant

  • Phototaxis assay with green algae

  • Protein content of beans – with Dr. McCarthy - spectrophotometric assay

    • quantitative – more use of Excel

    • graphing, statistics, etc. - all huge plusses

  • Idea for Drosophila mutant workup: from Virtual fly to “Flybase” bioinformatics


Not a replacement
Not a replacement! phenotype, e.g. cell division mutant

  • But an addition to the wet lab approach

  • Substitution of simulations at the exclusion of wet lab experience is dangerous, from the standpoint of student education

  • The units are merely new tools


July 2007
July 2007 phenotype, e.g. cell division mutant

  • Hands on workshop with local biology educators to disseminate the ideas

  • Set up local “teaching collaboratory”


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