Course 4541.569: Biomolecular Computation

(Advanced AI)

 

School of Computer Science and Engineering,

Graduate Programs in Bioinformatics,

Brain Science, and Cognitive Science
Seoul National University

Instructor

Byoung-Tak Zhang

TA

Soo-Yong Shin

Classroom

302-209

Time

Wed, 10:30 ~ 11:45,   Fri,  10:30 ~ 11:45

References

  • Jacques Monod, Change and Necessity: On the Natural Philosophy of Modern Biology, Knopf Press, 1971 (Penguin Books, 1997)
  • Manfred Eigen, Laws of the Game: How the Principles of nature Govern Chance, Princeton University Press, Princeton, 1993
  • Christian de Duve, Life Evolving: Molecules, Mind, and Meaning, Oxford University Press, 2002
  • Philip Ball, Stories of the Invisible: A Guided Tour of Molecules, Oxford University Press, 2001.
Requirements

  • Reports (Proposal 5%, Midterm 15%, Final 40%)

  • Oral Presentation (20%)

  • Active Participation in Discussion (20%)

Objectives
  • Understanding the biomolecular mechanisms underlying learning, memory, and evolution
  • Studying the principles and applications of biomolecular computing
  • Acquiring the technologies for biomolecular information processing
  • Understanding the convergence of science and technology in frontier research
  • Practicing skills for writing and presenting technical papers and reports
Term Project

  • Schedule
Date Main Subjects Ref. Due PPT
Basics and Principles
 Week 1.1

(March 5)

Introduction to the Course

  •  Course objective

  •  Schedule

  •  Plan for exam

  •  Plan for projects

J. Monod, 1971

 

M. Eigen, 1993

 

C. de Duve, 2002

  [PPT]
Week 1.2

(March 7)

Cell as a Molecular Computer

  •  What is a cell?

  •  Types of cells

  •  What's interesting about cells?

  •  Cell as a computer

    [PPT]
 Week 2.1

(March 12)

Biochemistry of DNA and RNA

  • Structure of DNA

  • From DNA to RNA

  • Structure of RNA

  • Kinds of RNA

    [PPT]
 Week 2.2

(March 14)

Proteins and Enzymes

  • From RNA to Proteins

  • Structure of Proteins

  • Enzymes

  • What Is Life?

    [PPT]
 Week 3.1

(March 19)

Biomolecular Computing: Principles

  • Paradigms of computation

  • Principles of biomolecular computing

  • Representation and operations

  • Examples and applications

Zhang

(IEEK-2002)

 

Reif

(NGC-2002)

  [PPT]
 Week 3.2

(March 21)

Biomolecular Computing: Technologies

  • Biochemical techniques

  • Nanotechnology

  • MEMS and Lab-on-a-chips

  • Bioinformatics

    [PPT]
Application Examples
 Week 4.1

(March 26)

Molecular Inference

  • Theorem proving with DNA molecules

  • Linear representation

  • Branched DNA and hairpin structures

  • Biochemical experimental results

Lee et al.

(DNA8-2002)

 

Lee et al.

(DNA9-2003)

5-page essay for the popular science books [PPT]
 Week 4.2

(March 28)

Molecular Optimization

  • Solving TSP by DNA Molecules

  • Adleman's approach to HPP

  • Solving the "real" TSP

  • Temperature gradient methods for TSP

Shin & Zhang

(CEC-99)

 

Lee et al.

(DNA8-2002)

 

Park et al.

(NICE-2002)

  [PPT]
 Week 5.1

(April 2)

Molecular Learning

  • Inductive learning by DNA computing

  • DNA representation of concept

  • Bio-lab experiments

  • Bead separation on a lab-chip

Lim et al.

(DNA8-2002)

 

Lim et al.

(DNA9-2003)

  [PPT]
 Week 5.2

(April 4)

Molecular Memory

  • Associative memory and DNA molecules

  • Storage and retrieval of cases in DNA molecules

  • Learning by concentration update

  • Reaction kinetics and simulation results

Jung

(MS-2003)

  [PPT]

 Week 6.1

(April 9)

Exam   Exam [PPT]
 Week 6.2

(April 11)

Term Projects Assignment List of papers   [PPT]
 Week 7.1

(April 16)

Cognitive Simulations

  • Logical inference with DNA molecules

  • Solving the Monkey-and-Banana problem

  • Cognitive models of low-level language processing

  • DNAnagram: A DNA-based anagram solver

  • Representing phonological rules in DNA

Park et al.

(2003)

 

Lee et al.

(2003) 

  [PPT] 
 Week 7.2

(April 18)

Biological Simulations

  • Pattern recognition

  • Encoding 2D patterns in DNA strands

  • DNA tree structures

  • Modeling synaptic transmission

  • Molecular neural networks

Chung et al.

(2003)

 

Ku et al.

(2003) 

  [PPT]
Theories and Models
 Week 8.1

(April 23)

Biomolecular Computing: Theories

  • Unconventional models of computation

  • Particle theory of molecular computing

  • Gas phase and liquid phase

  • Particle computing and field theory

    [PPT]
 Week 8.2

(April 25)

No lecture

  • KISS-2003 conference

    [PPT]
 Week 9.1

(April 30)

Thermodynamics and Information Theory

  • Maxwell's demon

  • Entropy and free energy

  • Statistical physics

  • Information theory

 

  [PPT]
 Week 9.2

(May 2)

Chemical Kinetics and Reaction Dynamics

  • Enzymes

  • Chemical kinetics

  • Reaction dynamics

  • Probabilistic graphical models

 

Term project 1st draft [PPT]
 Week 10.1

(May 7)

Theory of Collectively Autocatalytic Sets

  • Nude-gene theory

  • Coconstructing systems

  • Collectively autocatalytic sets

  • Self-constructing open thermodynamic systems

 

  [PPT]
 Week 10.2

(May 9)

Beyond DNA: RNA Computing

  • The RNA world and the origin of life

  • Directed evolution

  • Chemical evolution

  • Molecular evolution

  • Eigen's Hypercycle

 

  [PPT]
 Week 11.1

(May 14)

Protein Computing

  • Antibody-antigen

  • Peptide computing

  • Immunochemical computing

  • Protein folding and computation

 

  [PPT]
 Week 11.2

(May 16)

Genetic and Signaling Biomolecular Networks

  • Gene regulation networks

  • Toggle switches

  • Synthesis of logic circuits within the cell

  • Signal transduction networks

 

  [PPT]
Term Project Presentations
 Week 12.1

(May 21)

Term Project Presentations I

  • Four presentations 20 minutes each

  • 한석민, 김홍석, (남진우, 신기루), (김수동, 이은석)

 

  [PPT]
 Week 12.2

(May 23)

Term Project Presentations II

  • Four presentations 20 minutes each

  • (남진우, 정제균), 김정래, (김병희, 현우길), 장하영

 

  [PPT]
 Week 13.1

(May 28)

Term Project Presentations III

  • Four presentations 20 minutes each

  • 나의택, 이희공, 정호진, (나머지 사람들)

 

  [PPT]
Advanced Technologies
 Week 13.2

(May 30)

Nanostructures and Self-Assembly

  • Self-assembly

  • DNA nanostructures

  • DNA motors and actuators

  • Supramolecular chemistry

 

  [PPT]
 Week 14.1

(June 4)

Microreaction Techonology

  • MEMS and BioMEMS

  • Microfluidics and lab-on-a-chip

  • Microreactor networks

  • Machine learning chips

 

  [PPT]
 Week 14.2

(June 6)

Discussion

  • From biomolecular networks to cellular networks

  • Bioinformatics for biocomputing

 

  [PPT]

 Week 15.1

(June 11)

Outlook

 

Final report of the term project  

This page is maintained by Soo-Yong Shin (syshin@bi.snu.ac.kr), Laste update : April 14, 2003

 

[PPT]