marc d. riedel assistant professor, ece university of minnesota ee 5393: circuits, computation and...

Marc D. RiedelAssistant Professor, ECE University of Minnesota

EE 5393: Circuits, Computation and BiologyEE 5393: Circuits, Computation and Biology

ORAND AND

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1f 2f 3f

“Minnesota Farmer”

• 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!

Who is this guy?

“Minnesota Farmer”

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

Who is this guy?

He’s a human-bacteria hybrid:

vs.

• only 1 trillion human cells of 210 different types.

[like all of us]

“Minnesota Farmer”

Who is this guy?What’s in his gut?

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

He’s a human-bacteria hybrid:

vs.

• only 1 trillion human cells of 210 different types.

[like all of us]

About 3 pounds of bacteria!

What’s 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

flagellum

Bacterial Motor

Bacterial Motor

Electron Microscopic Image

“Stimulus, response! Stimulus response! Don’t you ever think!”

We should put these critters to

work…

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 …

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

• Quantitative modeling.• Mathematical analysis.• Incremental and iterative design changes.

Engineering Design

Building Digital Circuits

Intel 4004(1971)

Intel “Nehalem”(2008)

~2000 gates

~2 billion gates

inputs outputs

• Design is driven by the input/output specification.• CAD tools are not part of the design process; they are

the design process.

Building Digital Circuits

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1x

2x

mx

digital circuit

…

…

…

...

Synthetic Biology

• Cellulosic ethanol (Nancy Ho, Purdue, ’04)

• Anti-malarial drugs (Jay Keasling, UC Berkeley, ‘06)

• Tumor detection (Chris Voigt, UCSF ‘06)

Feats of synthetic bio-engineering:

Strategy: apply experimental expertise; formulate ad-hoc designs; perform extensive simulations.

From ad hoc to Systematic…

Claude E. Shannon1916 –2001

“A Mathematical Theory of Communication,” Bell System Technical

Journal, 1948.

Basis of information theory, coding theoryand all communication systems.Basis of all digital computation.

“A Symbolic Analysis of Relay and Switching Circuits,”

M.S. Thesis, MIT, 1937

[computational] Synthetic Biology[computational] Analysis

“There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2004

BiologicalProcess

Molecular Inputs

Molecular Products

KnownKnown

UnknownKnown /Unknown

UnknownGiven

Artificial Life

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

Going from reading genetic codes to writing them.

Artificial Life

Going from reading genetic codes to write them.

Moderator: “Some people have accused you of playing God.”

J. Craig Venter:“Oh no, we’re not playing.

Biochemistry in a Nutshell

DNA: string of n nucleotides (n ≈ 109)

... ACCGTTGAATGACG...

},,{},,,{ 2013 aaGTCA

Nucleotides:

Amino acid: coded by a sequence of 3 nucleotides.

Proteins: produced from a sequence of m amino

acids (m ≈ 103).

},,,{ GTCA

protein},,{ 201 maa

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 biochemistry…

Novel biological functions…

Jargon vs.Terminology

“Now this end is called the thagomizer, after the late Thag Simmons.”

The Computational Landscape“There are known ‘knowns’; and there are unknown

‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

Semiconductors:exponentially smaller, faster, cheaper – forever?

1 transistor (1960’s)2000 transistors(Intel 4004, 1971)

800 million transistors(Intel Penryn, 2007)

The Computational Landscape

• Abutting true physical limits.

• Cost and complexity are starting to overwhelm.

“There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

Semiconductors:exponentially smaller, faster, cheaper – forever?

The Computational Landscape

• Multiple cores?• Parallel Computing?

Potential Solutions:

“There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

The Computational Landscape

b

a?

• Novel Materials?

Potential Solutions:

• Novel Function?

“There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

gene

The Computational Landscape“There are known ‘knowns’; and there are unknown

‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

RNAp outputprotein

repressorprotein

The Computational Landscape

gene

“There are known ‘knowns’; and there are unknown ‘unknowns’; but today I’ll speak of the known ‘unknowns’.”

– Donald Rumsfeld, 2002

RNAp

Biological computation?

nada

Research Activities in my Lab

• 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.

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: ?

Research Activities in my Lab

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

• We’re studying the concepts, mechanisms, and dynamics of intracellular biochemistry.

• We’re writing computer programs for analyzing and synthesizing these dynamics.

CircuitsCircuits

BiologyBiology

Two Made-Up Facts[well, abstractions, really…]

1x

2x

g

Logic Gates

Biochemical Reactions

+

“AND” gate

0001

1x

2x

g0011

0101

1x 2x g

Logic Gates

“XOR” gate

0011

0101

0110

1x

2x

g

1x 2x g

Logic Gates

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),,( 12 mxxf a

),,( 1 mn xxf a

inputs outputs

Digital Circuit

1x

2x

mx

circuit

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),,( 11 mxxf a

),,( 12 mxxf a),,( 1 mxxf a

inputs outputs

1x

2x

mx

circuit gate

Digital Circuit

1x

2x

3x

4x

5x

6x

NAND

OR

ANDAND

AND

NOR

1

0

0

1

1

1

1

0

1

0

0

1

Digital Circuit

My PhD Dissertation[yes, in one slide…]

x1

x1

x1

x1

x2

x2

x3

x3

It’s not a bug, it’s a feature.

circuit0

1

Characterize probability of outcomes.

inputs outputs

Model defects, variations, uncertainty, etc.:

Current Research

circuit

inputs outputs

Model defects, variations, uncertainty, etc.:

0,1,1,0,1,0,1,1,0,1,…

1,0,0,0,1,0,0,0,0,0,…

p1 = Prob(one)

p2 = Prob(one)

Current Research

circuit

inputs outputs

Model defects, variations, uncertainty, etc.:

51

52

Current Research

Biochemical Reactions

9

6

7

cellprotein count

+

8

5

9

Biochemical Reactions

+

+

+

slow

medium

fast

Bacteria are engineered to produce an anti-cancer drug:

Design Scenario

drugtriggering compound E. Coli

Bacteria invade the cancerous tissue:

cancerous tissue

Design Scenario

cancerous tissue

The trigger elicits the bacteria to produce the drug:

Design Scenario

Bacteria invade the cancerous tissue:

cancerous tissue

Problem: patient receives too high of a dose of the drug.

Design Scenario

The trigger elicits the bacteria produce the drug:

Design Scenario

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

Constraints:

• Control quantity of drug that is produced.

Requirement:

Conceptual design problem.

cancerous tissue

Approach: elicit a fractional response.

Design Scenario

produce drug

triggering compound E. Coli

Approach: engineer a probabilistic response in each bacterium.

with Prob. 0.3

don’t produce drugwith Prob. 0.7

Synthesizing Stochasticity

Engineering vs. Biology vs. Mathematics

Dilbert Beaker Papa

Communicating Ideas

Domains of Expertise

• Vision• Language• Abstract Reasoning• Farming

Human

Circuit

• Number Crunching

• Mining Data• Iterative

Calculations

“A person's mental activities are entirely due to the behavior of nerve cells, glial cells, and the atoms, ions, and molecules that make them up and influence them.”

– Francis Crick, 1982

Astonishing Hypothesis

“That the astonishing hypothesis is astonishing.”

– Christophe Koch, 1995

The Astonishing Part

Circuits & Computers as a Window into our Linguistic Brains

CircuitBrainConceives of circuits and

computation by “applying” language.

Lousy at all the tasks that the brain that

designed it is good at (including language).

?

If You Don’t Know the Answer…