EE 5940: Circuits, Computation and Biology

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EE 5940 Circuits, Computation and Biology
Marc D. Riedel
Assistant Professor, ECE University of Minnesota
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Who is this guy?

• Most of the cells in his body are not his own!
• Most of the cells in his body are not even human!
• Most of the DNA in his body is alien!

Minnesota Farmer
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Who is this guy?
Hes a human-bacteria hybrid
like all of us

• 100 trillion bacterial cells of at least 500
  different types inhabit his body.

vs.

• only 1 trillion human cells of 210 different
  types.

Minnesota Farmer
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Who is this guy?
Whats in his gut?
Hes a human-bacteria hybrid
like all of us

• 100 trillion bacterial cells of at least 500
  different types inhabit his body.

vs.

• only 1 trillion human cells of 210 different
  types.

Minnesota Farmer
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Whats in his gut?
E. coli, a self-replicating object only a
thousandth of a millimeter in size, can swim 35
diameters a second, taste simple chemicals in its
environment, and decide whether life is getting
better or worse. Howard C. Berg
About 3 pounds of bacteria!
flagellum
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Bacterial Motor
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Bacterial Motor
Electron Microscopic Image
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The (nano) Structural Landscape
You see things and you say Why? But I dream
things that never were and I say Why not?"
George Bernard Shaw,
1925

Novel Materials
Novel biological functions
Novel biochemistry
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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
Semiconductorsexponentially smaller, faster,
cheaper forever?
2000 transistors(Intel 4004, 1971)
800 million transistors(Intel Penryn, 2007)
1 transistor (1960s)
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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
Semiconductorsexponentially smaller, faster,
cheaper forever?

• Abutting true physical limits.
• Cost and complexity are starting to overwhelm.

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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
Potential Solutions

• Multiple cores?
• Parallel Computing?

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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
Potential Solutions

• Novel Materials?

?

• Novel Function?

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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
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The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
repressor protein
Biological computation?
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Research Activities in my Lab
Our research activities encompass topics in logic
synthesis and verification, as well as in
synthetic and computational biology. A broad
theme is the application of expertise from the
realm of circuit design to the analysis and
synthesis of biological systems. Current projects
include
?

• The concurrent logical and physical design of
  nanoscale digital circuitry.
• The synthesis of stochastic logic for robust
  polynomial arithmetic.
• Feedback in combinational circuits.
• High-performance computing for the stochastic
  simulation of biochemical reactions.
• The analysis and synthesis of stochasticity in
  biochemical systems.

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Research Activities in my Lab
Circuits

• Were studying the mathematical functions for
  digital circuits.
• Were writing computer programs to automatically
  design such circuits.

Biology

• Were studying the concepts, mechanisms, and
  dynamics of intracellular biochemistry.
• Were writing computer programs for analyzing and
  synthesizing these dynamics.

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Two Made-Up Facts
well, abstractions, really
Logic Gates
Biochemical Reactions
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Logic Gates
AND gate
0
0
0
1
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Logic Gates
XOR gate
0
0
0
0
1
1
1
0
1
1
1
0
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Digital Circuit
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Digital Circuit
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Digital Circuit
1
1
0
1
0
0
0
1
0
1
1
1
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My PhD Dissertation
yes, in one slide
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Current Research
Model defects, variations, uncertainty, etc.
0
1
Characterize probability of outcomes.
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Current Research
Model defects, variations, uncertainty, etc.
p1 Prob(one)
0,1,1,0,1,0,1,1,0,1,
1,0,0,0,1,0,0,0,0,0,
p2 Prob(one)
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Current Research
Model defects, variations, uncertainty, etc.
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Biochemical Reactions
cell
protein
count
9
8
6
5
7
9
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Biochemical Reactions
slow
medium
fast
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Example Exponentiation
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Exponentiation
M
given
want
(m)
(n)
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Design Scenario
Bacteria are engineered to produce an anti-cancer
drug
triggering compound
drug
E. Coli
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Design Scenario
Bacteria invade the cancerous tissue
cancerous tissue
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Design Scenario
The trigger elicits the bacteria to produce the
drug
Bacteria invade the cancerous tissue
cancerous tissue
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Design Scenario
The trigger elicits the bacteria produce the
drug
Problem patient receives too high of a dose of
the drug.
cancerous tissue
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Design Scenario
Conceptual design problem.
Constraints

• Bacteria are all identical.
• Population density is fixed.
• Exposure to triggering compound is uniform.

Requirement

• Control quantity of drug that is produced.

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Design Scenario
Approach elicit a fractional response.
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Synthesizing Stochasticity
Approach engineer a probabilistic response in
each bacterium.
produce drug
with Prob. 0.3
triggering compound
dont produce drug
with Prob. 0.7
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Synthesizing Stochasticity
Generalization engineer a probability
distribution on logical combinations of different
outcomes.
A
with Prob. 0.3
B
with Prob. 0.2
cell
C
with Prob. 0.5
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Synthesizing Stochasticity
Generalization engineer a probability
distribution on logical combinations of different
outcomes.
A
with Prob. 0.3
B
with Prob. 0.2
cell
C
with Prob. 0.5
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Synthesizing Stochasticity
Generalization engineer a probability
distribution on logical combinations of different
outcomes.
X
Y
cell
Further program probability distribution with
(relative) quantity of input compounds.
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Engineering vs. Biology vs. Mathematics
Papa
Beaker
Dilbert
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Its not a bug, its a feature.
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Jargon vs.Terminology
Now this end is called the thagomizer, after the
late Thag Simmons.
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Communicating Ideas
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Domains of Expertise

• Vision
• Language
• Abstract Reasoning
• Farming

• Number Crunching
• Mining Data
• Iterative Calculations

Human
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Circuits Computers as a Window into our
Linguistic Brains
Conceives of circuits and computation by
applying language.
?
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If You Dont Know the Answer
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EE5940 Course Information

• (Meaningless) Title Special Topics in E.E. I
• (Actual) Title Circuits, Computation and
  Biology
• Instructor Prof. Marc Riedel office EE/CSi
  4-167 tel [phone] email mriedel_at_umn.edu
• Credits 3
• Meeting time Tues. Thurs., 1245pm 200pm
• Office hours Wed., 3pm, EE/CSi 4-167
• Location Mech. E. 108
• Prerequisites none.
• Textbook none.
• Website www.cctbio.ece.umn.edu under Courses

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Grading

• 10 in-class quizzes
• 70 for 7 homework sets (every two weeks)
• 20 for student presentationsPresentations will
  be 20 mins., last two weeks of the semester

No Exams
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Quizzes

• 10 such quizzes, each worth 1.
• Given at the beginning of some classes
  (unannounced).
• Based on material covered on previous classes.
• Very basic questions.
• Can complete
• at the beginning of class
• during office hours
• any other time, in any order before the end of
  semester.
• If you answer incorrectly, try again (as many
  times as you like).

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Homeworks

• Due at 200pm (will not be accepted after
  340pm)
• Generally five problems, each worth 2.
• Based either on material covered in class or
  that in papers assigned (emailed as pdfs).
• Written solutions (no programming or lab work)
• Emphasis on clarity as well as correctness.
• Some problems marked as collaboration ok
  others as no collaboration.

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Collaboration

• Collaboration ok problems
• You may discuss the problems beforehand with
  other students (but not with former students of
  the class).
• Once you begin writing the solution to any
  problem, you may not discuss any further.
• No collaboration problems
• You cannot discuss the problems at all with other
  students (but you may discuss these with the
  instructor).

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Student Presentations

• Can select a paper from a list that will be
  provided.
• Or, can choose a topic covered in class.
• Or can choose a topic of your own (any topic at
  all, even if only tangentially related to
  course).
• Will present the ideas in a 20-minute
  slotGrade
• 10 for clarity of explanation
• 10 for novel research ideas
• Best to focus on a specific, conceptual idea.