circuit engineers doing biology marc d. riedel assistant professor, electrical and computer...

Circuit Engineers Doing BiologyCircuit Engineers Doing Biology

Marc D. RiedelAssistant Professor, Electrical and Computer Engineering

University of Minnesota

Café Scientifique

A Discourse on the Changing Landscape of Scientific ResearchA Discourse on the Changing Landscape of Scientific Research

Hosted by the Bell Museum of Natural History

At the Bryant-Lake Bowl

“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?


• 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]


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

Nov. 20, 2007 Marc Riedel, Café Scientifique 8

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…

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’.”


Semiconductors:exponentially smaller, faster, cheaper – forever?


• Multiple cores?• Parallel Computing?

Potential Solutions:




b

a?

• Novel Materials?

Potential Solutions:

• Novel Function?



gene

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

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


RNAp outputprotein

repressorprotein


gene



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


),,( 11 mxxf a

),,( 12 mxxf a

),,( 1 mn xxf a

inputs outputs

Digital Circuit

1x

2x

mx

circuit


),,( 1 mn xxf a

),,( 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

circuit0

1

Characterize probability of outcomes.

inputs outputs

Model defects, variations, uncertainty, etc.:

Current Research

circuit

inputs outputs


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


51

52

Current Research



9

6

7

cellprotein count

+

8

5

9



+

+

+

slow

medium

fast

Example: Exponentiation

“Every task will take twice as long as expected – even if the Riedelian Law of Productivity is taken into account.”

– That Great Procrastinator Riedel [midnight last night]

Riedelian Law of Productivity

n2222

n

M

ExponentiationM2given want

(m) (n)

Use working types a, b, n

sets n to onelet a be non-zero nana fast2

meda

let b be zero

sets n to M2

bmslow

nbnb 2v. fast

fastb

nn med.


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


Generalization: engineer a probability distribution on logical combinations of different outcomes.

cell

A with Prob. 0.3

B with Prob. 0.2

C with Prob. 0.5




cell

A and B with Prob. 0.3


B and C with Prob. 0.7

A with Prob. 0.3

B with Prob. 0.2

C with Prob. 0.5


cell

A and B with Prob. 0.3


B and C with Prob. 0.7

Further: program probability distribution with (relative) quantity of input compounds.

)/()Pr( 1 YXfA

)/()Pr( 2 YXfB

)/()Pr( 3 YXfC

X

Y


Engineering vs. Biology vs. Mathematics

Dilbert Beaker Papa

It’s not a bug, it’s a feature.

Jargon vs.Terminology

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

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…

circuit engineers doing biology marc d. riedel assistant professor, electrical and computer...

Documents

human cells

bacterial cells

bacterial motor slide

different types

minnesota farmer

berg flagellum slide

humanbacteria hybrid

bryantlake bowl slide