EE 5393: Circuits, Computation and Biology

1. AND OR AND Marc D. Riedel Assistant Professor, ECE University of Minnesota EE 5393: Circuits, Computation and Biology

2. Instructor Prof. Marc Riedel tel.: (612) 625-6086email:mriedel@umn.edu office: EE/CSi4-167 office hours: M. 1:00–3:00pm

3. Teaching Assistants YasamanAdibitel.:TBDemail:adibi002@umn.eduoffice: TBD office hours: none.

4. EE5393: Circuits, Computation, and Biology • Lecture: Wed. & Friday, 2:30–3:45pm Location: Keller Hall 3-230 • Prereqs: none • Textbooks: none • Website: http://tinyurl.com/ee5393

5. Grading • 20%Quizzes:11 quizzes (best 10 of 11 scores) • 80%Homeworks:5 homeworks(best 4 of 5 scores)

6. Astonishing Hypothesis The Astonishing Part: “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 “That the astonishing hypothesis is astonishing.” – Christophe Koch, 1995

7. Circuit Domains of Expertise • Vision • Language • Abstract Reasoning • Farming • Number Crunching • Mining Data • Iterative Calculations Human

8. Circuit Brain Lousy at all the tasks that the brain that designed it is good at (including language). Circuits & Computers as a Window into our Linguistic Brains Conceives of circuits and computation by “applying” language. ?

9. Language as a Window into the way the Brain Works Steven Pinker, Harvard

10. 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 isalien! “Minnesota Farmer”

11. Who is this guy? He’s a human-bacteria hybrid: • 100 trillion bacterial cells of at least 500 different types inhabit his body. [like all of us] vs. • only 1 trillion human cells of 210 different types. “Minnesota Farmer”

12. What’s in his gut? Who is this guy? He’s a human-bacteria hybrid: • 100 trillion bacterial cells of at least 500 different types inhabit his body. [like all of us] vs. • only 1 trillion human cells of 210 different types. “Minnesota Farmer”

13. 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 About 3 pounds of bacteria! flagellum

14. Bacterial Motor

15. Bacterial Motor Electron Microscopic Image

16. We should put these critters to work… “Stimulus, response! Stimulus response! Don’t you ever think!”

17. 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

18. Artificial Life Going from reading genetic codes to writing them. Moderator: “Some people have accused you of playing God.” J. Craig Venter:“Oh no, we’re not playing.

20. 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) called a “gene”.

21. + 2a c b + Design Abstraction Biochemical Reactions: rules specifying how types of molecules combine.

22. + Biomolecular Reactions cell/test tube types count 9 8 6 5 7 9 Discrete chemical kinetics; spatial homogeneity.

23. + + + Biomolecular Reactions Relative rates or (reaction propensities): slow medium fast Discrete chemical kinetics; spatial homogeneity.

24. Concepts vs. Jargon “Now this end is called the thagomizer, after the late Thag Simmons.”

25. BiologicalProcess [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 Molecular Inputs Molecular Products Known /Unknown Given Known Unknown Unknown Known

26. Protein-ProteinChemistry y [computational]Biochemistry Biochemical[computation] x z quantity quantities

27. Multiplication pseudo-code biochemical code

28. Exponentiation pseudo-code biochemical code

29. Raising-to-a-Power pseudo-code biochemical code

30. Multiplication

31. Biological Computation at the Populational Level How can we control the quantity of molecular product at the populational level?

32. Synthesizing Stochasticity Engineer a probabilistic response in each cell. product with Prob.0.3 trigger no product with Prob.0.7

33. Biological Computation at the Populational Level Obtain a fractional response.