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EE 5393: Circuits, Computation and Biology

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Title: EE 5393: Circuits, Computation and Biology


1
EE 5393 Circuits, Computation and Biology
Marc D. Riedel
Assistant Professor, ECE University of Minnesota
2
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
3
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
4
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
5
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
6
Bacterial Motor
7
Bacterial Motor
Electron Microscopic Image
8
We should put these critters to work
Stimulus, response! Stimulus response! Dont you
ever think!
9
Synthetic Biology
  • Positioned as an engineering discipline.
  • Novel functionality through design.
  • Repositories of standardized parts.
  • Driven by experimental expertise in particular
    domains of biology.
  • Gene-regulation, signaling, metabolism, protein
    structures

10
Building Bridges
"Think of how engineers build bridges. They
design quantitative models to help them
understand what sorts of pressure and weight the
bridge can withstand, and then use these
equations to improve the actual physical model.
In our work on memory in yeast cells we really
did the same thing.
Pam Silver, Harvard 2007
Engineering Design
  • Quantitative modeling.
  • Mathematical analysis.
  • Incremental and iterative design changes.

11
Building Digital Circuits
Intel 4004(1971)
2000 gates
Intel Nehalem(2008)
2 billion gates
12
Building Digital Circuits
  • Design is driven by the input/output
    specification.
  • CAD tools are not part of the design process
    they are the design process.

13
Synthetic Biology
Feats of synthetic bio-engineering
  • Cellulosic ethanol (Nancy Ho, Purdue, 04)
  • Anti-malarial drugs (Jay Keasling, UC Berkeley,
    06)
  • Tumor detection (Chris Voigt, UCSF 06)

Strategy apply experimental expertise formulate
ad-hoc designs perform extensive simulations.
14
From ad hoc to Systematic
A Symbolic Analysis of Relay and Switching
Circuits,M.S. Thesis, MIT, 1937
Claude E. Shannon1916 2001
A Mathematical Theory of Communication, Bell
System Technical Journal, 1948.
Basis of all digital computation.
Basis of information theory, coding theoryand
all communication systems.
15
computational Synthetic Biology
computational Analysis
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2004
Molecular Inputs
Molecular Products
Known /Unknown
Given
Known
Unknown
Unknown
Known
16
Artificial Life
Going from reading genetic codes to writing them.
US Patent 20070122826 (pending)The present
invention relates to a minimal set of
protein-coding genes which provides the
information required for replication of a
free-living organism in a rich bacterial culture
medium. J. Craig
Venter Institute
17
Artificial Life
Going from reading genetic codes to write them.
Moderator Some people have accused you of
playing God. J. Craig VenterOh no, were not
playing.
18
Biochemistry in a Nutshell
Nucleotides
DNA string of n nucleotides (n 109)
... ACCGTTGAATGACG...
Amino acid coded by a sequence of 3 nucleotides.
Proteins produced from a sequence of m amino
acids (m 103).
19
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
20
Jargon vs.Terminology
Now this end is called the thagomizer, after the
late Thag Simmons.
21
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)
22
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.

23
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?

24
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?

25
The Computational Landscape
There are known knowns and there are unknown
unknowns but today Ill speak of the known
unknowns. Donald
Rumsfeld, 2002
26
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?
27
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.

28
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29
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.

30
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31
Two Made-Up Facts
well, abstractions, really
Logic Gates
Biochemical Reactions
32
Logic Gates
AND gate
0
0
0
1
33
Logic Gates
XOR gate
0
0
0
0
1
1
1
0
1
1
1
0
34
Digital Circuit
35
Digital Circuit
36
Digital Circuit
1
1
0
1
0
0
0
1
0
1
1
1
37
My PhD Dissertation
yes, in one slide
38
Its not a bug, its a feature.
39
Current Research
Model defects, variations, uncertainty, etc.
0
1
Characterize probability of outcomes.
40
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)
41
Current Research
Model defects, variations, uncertainty, etc.
42
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43
Biochemical Reactions
cell
protein
count
9
8
6
5
7
9
44
Biochemical Reactions
slow
medium
fast
45
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46
Design Scenario
Bacteria are engineered to produce an anti-cancer
drug
triggering compound
drug
E. Coli
47
Design Scenario
Bacteria invade the cancerous tissue
cancerous tissue
48
Design Scenario
The trigger elicits the bacteria to produce the
drug
Bacteria invade the cancerous tissue
cancerous tissue
49
Design Scenario
The trigger elicits the bacteria produce the
drug
Problem patient receives too high of a dose of
the drug.
cancerous tissue
50
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.

51
Design Scenario
Approach elicit a fractional response.
52
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
53
Engineering vs. Biology vs. Mathematics
Papa
Beaker
Dilbert
54
Communicating Ideas
55
Domains of Expertise
  • Vision
  • Language
  • Abstract Reasoning
  • Farming
  • Number Crunching
  • Mining Data
  • Iterative Calculations

Human
56
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57
Circuits Computers as a Window into our
Linguistic Brains
Conceives of circuits and computation by
applying language.
?
58
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