SYMBIOSIS ETSUHHMI2007

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Multidisciplinary Collaboration Lessons Learned
by Mathematical Biology Educator
John R. Jungck International Union of Biological
Sciences Society for Mathematical
Biology BioQUEST Curriculum Consortium Beloit
College
SYMBIOSISETSU-HHMI-2007
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The BioQUEST Curriculum Consortium is funded by
HHMI, NSF, and EOT-PACI Howard Hughes Medical
Institute, Division of Undergraduate Education,
National Science Foundation, and Education
Outreach and Training - Partnership for Advanced
Computing Infrastructure
Previous major funding Annenberg
Project/Corporation for Public Broadcasting Founda
tion for Microbiology Beloit College University
of Chicago Center for Biology Education,
University of Wisconsin - Madison Apple
Computer Pew Midstates Science Mathematics
Consortium
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• HHMI subcontract from Claudia Neuhauser,
• HHMI Fellow Chair, Ecology Evolution,
• College of Bioloogical Sciences, University of
  Minnesota

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Mathematical biology education and a response to
NRCs Bio 2010 recommendations
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"Geometry is a skill of the eyes and the hands as
well as the mind." - Jean Pedersen
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Image Analysis to Fractal Dimension
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Biological Cellular Automata Laboratory (BioCA
Lab)

• Author(s) John Jungck, Beloit CollegeJennifer
  Spangenberg, Washington State University

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Three Boxes
How do students interact with the mathematical
model underlying the biology?
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Central role of problem-solving environments
powerful tools that develop professional
skills interactive open-ended
challenging research-related depth of
analysis contemporary empowering lend
themselves to collaborative learning
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50 Years After Brown vs. Board of
EducationMathematics Education is a Civil
Rights Issue
Today . . . the most urgent social issue
affecting poor people and people of color is
economic access. In todays world, economic
access and full citizenship depend crucially on
math and science literacy. I believe that the
absence of math literacy in urban and rural
communities throughout this country is an issue
as urgent as the lack of Black voters in
Mississippi was in 1961.
Moses, R. P. (2001). Radical equations Math
literacy and civil rights.
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Underrepresented Minorities in Mathematics
AAAS 2005 Annual Meeting, Washington D.C.

• Carlos Castillo-Chavez
• Joaquin Bustoz Jr. Professor
• Arizona State University
• February 20, 2005

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MTBI 1996
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MTBI 2003
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Nine Years of MTBI Results

• Since 1996 MTBI has mentored 232 undergraduates.
• Approximately 12 Latinos in graduate school per
  year (15 total underrepresented minority
  students)
• Since 1996 MTBI students have produced 89 papers,
  each years papers are published as technical
  reports--many published articles.

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National Research Council Bio 2010 Transforming
Undergraduate Education for Future Research
Biologists Recommendation 2 Concepts,
examples, and techniques from mathematics,
should be included in biology courses. Faculty
in biology, mathematics, and physical sciences
must work collaboratively to find ways of
integrating mathematics into life science
courses ISBN 0-309-08535-7 (2003)
Recommendation 1 Those selecting the new
approaches should consider the importance of
mathematics,
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Meeting the Challenges Education Across the
Biological, Mathematical, and Computer Sciences

• Sponsored by
• National Science Foundation
• National Institute of General Medical Sciences
• American Association for the Advancement of
  Science
• Mathematical Association of America
• American Society for Microbiology
• pub.nigms.nih.gov/challenges/
• www.maa.org/mtc/

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Mathematics in Biology CurriculaWHY?
Lynn Arthur Steen, editor Math Bio 2010
Linking Undergraduate Disciplines Mathematics
Association of America (2005).

• RESPECT
• CONSISTENCY
• EMPOWERMENT

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Two Challenges

• (1) Deluge of data
• (2) Working together, Working apart

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Tsunami of Data
Tsunami of DataTerrabytesPerDay
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www.calacademy.org/.../ stories/horizons.html.
Kathleen M. Wong. Food Web Sandwich
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A more comprehensive yeast protein interaction
network
Deletion phenotype Red lethal Green
non-lethal Orange slow growth Yellow unknown

• An example of a scale-free network
• Most nodes have few connections
• A small number of nodes (network hubs) are
  connected to a large number of other notes

Source Jeong H et al (2004) Nature 41141-42
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Working Together, Working Apart
Participation Not just PIs Post-docs Graduate
Under- graduate students Technicians More
democratic Creativity, Innovation Less
isolation NIH Syndrome (Not In- vented Here)
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Mayo Clinic Model
Bioinfor-matics
Bioinfor-matics

• Surgery

Oncology
Pathol-ogy
Epidemi-ology
Applied Mathematics
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Working Together, Working Apart

• Synergisms
• Specializations provide expertise
• Respecting difference
• Tolerance

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Collaborative Mathematical Modeling
Top-Down ODEs PDEs (Symbolic Algebra Packages)
Engineering Control Nonlinear Feedback Hysteresis
(Stella, Simul, Extend)
Statistics Multivariate Resampling
(bootstrapping, etc.) Bayesian
Bottom-Up Cellular Automata Individual-Based
Modeling Particle-Based Modeling
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PAYOFF
Research
R I S K
Cf Dunbar, McGill University
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My HARD Lessons Learned

• Most valuable lessons have mostly been from
  learning from mistakes Ive made
• Collaborate, collaborate, collaborate!
• Remain flexible, adaptable, open
• Embrace serendipity
• Seek general, robust solutions (dont think that
  any project deserves only a one-time, quick and
  dirty solution - too many times Ive had to start
  all over again)
• Human resources are more important than
  technological resources

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Lost time KE approach to AI

• Mycin

SYNCHEM A final example (final only because
there is a limit to patience and energy, not
because further examples would be hard to find)
in a paper on SYNCHEM, a program that generates
paths for the synthesis of chemical compounds,
Gelernter and his colleagues claim that it should
be given credit for true intelligence because
From the beginning SYNCHEM always performed
above our reasonable expectations at each stage
of its development. (How reasonable their
expectations were if they always proved wrong, is
a question they do not consider.) Here it is the
surprise of the program designers themselves,
rather than that of a disinterested observer or
interrogator, that is offered as evidence of AI.
One can only imagine how much more intelligence
would have to be imputed to the program if its
designers were even more forgetful or lacking in
insight than they were.
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Contemporary AI

• Genetic Algorithms
• Neural Networks
• Fuzzy Logic
• Evolved not designed, biological metaphors
  evolution on a rugged adaptive landscape
  learning populations of rules recombinations,
  selection

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The mission is only a success if all groups
succeed.

• Four teams of teams
• Biology
• Mechanical Engineering
• Electrical Engineering
• Rocket Science

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Popular Mechanics -- 1954
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Look at a successful wish listcomputers

• 1968 Goal
• 1 million pixels
• 1 million instructions per second
• 1 megabyte storage
• 1 megabyte RAM
• Broad band large enough to transmit a full length
  movie in a minute

• 2007 laptop
• 1280 X 854 1,093,120
• 300 million instructions per second
• 60 Gigabyte hard drives are normative
• 2 Gigabyte RAM is normative
• Pipe still too small to download full length
  movies

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The Impact of Technological Change
power
1 billion PCs
1 billion PCs
1977
2002 2008
cost size
Gartner Dataquest, 2002
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Prediction

• In 2020 every laptop will be able to be viewed in
  full 4D,
• Vis 5D will be standard,
• and, have the power of a supercomputer
• But even if the technology is there,
• will biologists use it?
• A challenge to us!

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Why 2020?
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Microsoft Science 2020 report
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What mathematical reasoning should we expect
biologists to develop?
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The Challenges for 2020 STUDENTS

• Multivariate
• Multicausal
• Multidimensional
• Nonlinear
• Multi-scale
• Analyses of Complex Data

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Where are we now? Where do we need to go?

• General biology texts
• have less than 3 equations
• Rarely have quantitative data
• Graph complexity primarily linear
• No quantitative problems

• Biology education that uses calculus, discrete
  mathematics, statistics
• Quantitative problem solving throughout
• Modeling top down, bottom up, nonlinear feedback
• Deal with complexity of terabytes of data per day

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How close is 2020?

• Todays kindergarden student will be in college
  in 2020
• In other words, the student of tomorrow is
  already in school!
• Will biology education be as similar as 1994 was
  to 2007?

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VIII. Conclusion

• For Yesterday is but a Dream
• And To-morrow only a Vision
• But To-day well lived makes
• Every Yesterday a Dream of Happiness,
• And every Tomorrow, a Vision of Hope.
• - Kalidasa
• Indian poet and philosopher

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Staying with Tradition and Seeing ChangeAn
Anthropologists Advice

• there are a good many more ways of getting it
  wrong than getting it right, and one of the most
  common ways of getting it wrong is through
  convincing ourselves that we have gotten it right
  
• - Clifford Geertz