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Research lecture (CR)

Molecular programming: Theory & wet-lab experiments

Presentation

In this lecture, we will overview the various approaches to the uprising field of Molecular programming where one uses algorithms to design real molecules that processes information algorithmically. We will explore in details the various theoretical models, their complexity and expressiveness, learn how to program them and survey their experimental realizations, in particular how to design algorithmically these molecules for real. We will have you take part to real wet-lab experiments where we will design molecules executing a (simple) program for us and observe the nanoscopic result of their execution (usually only about few 100nm large) thru atomic force microscope (DNA origami) and fluorescence microscopy (DNA circuit). Wet-lab experiments will be conducted in collaboration with the biology & physics departments.

Outline

  • DNA as information processing material
  • Tile assembly model : Theory & experiments
  • Strand displacement circuits: Theory & experiments
  • Oritatami, a computational model for co-transcriptional folding: Theory & experiments
  • Wetlab experiments: making a DNA origami from scratch, making a DNA strand displacement circuit from scratch

Schedule

  • Thursdays morning (Room B1, ENS de Lyon Monod 4th floor)
    • 8:45-10:45: Lecture
    • (15 min break)
    • 11:00-12:00: Exercises session
  • Dates: 17/10, 24/10, 7/11 (learn how to design DNA orgami), 14/11 (vote for the origami to order for lab experiment), 21/11, 28/11 (wetlab experiments), 5/12, 12/12, 19/12, 9/1 14:00-16:00 (Final exam)
  • No prior experience on experiments required

Internship proposals

Past Lectures summary

Lecture 9 (2019.12.19 - Last): Oritatami Shapes & Strand displacement boolean circuits

  • Oritatami: building shapes [ Slides ]
    • The problem
    • Some impossible shapes
    • Scaling schemes
    • Algorithm for scales Bn≥3
    • Filling a pseudo-hexagon
    • Bead type set for tight Oritatami systems
    • Algorithm for scales An≥5
    • Algorithm for scale A4
    • Algorithm for scale A3
    • Time anomalies and how to fix them
  • Strand displacement boolean circuits [ Slides ]
    • DNA Strand displacement mechanism
    • Some basic of thermodynamics [ Slides ]
    • Reading with fluophore
    • Dealing with leaks
    • Double long domain [ Slides ]

Lecture 8 (2019.12.12): Oritatami: A computational model for co-transcriptional folding [ Slides A | Slides B ]

  • RNA Origami experiments
  • Oritatami model
  • A binary counter
  • Proving the correctness of the folding
  • Tag system and Oritatami simulating Turing machine efficiently
  • An Oritatami system simulating any Cellular Automaton
  • Exercise sessions [ HW4 | Solutions ]
    1. Window movie lemma :!:
    2. Oritatami

Lecture 7 (2019.12.05)

  • L'an 01: [ mkv | passwd: an01 ]

Lecture 6 (2019.11.28): Wetlab Experiments

Lecture 5 (2019.11.21): Intrinsic universality in tile assembly [ Slides ]

  • Intrinsic universality at T°2
  • The supercell, the probes
  • One (polygonal) tile is enough

Lecture 4 (2019.11.14): An experimental realisation of a universal computer (II) [ Slides ]

  • Examples of nanotube circuits
  • A 6-bits Turing universal nanotube circuit
  • Minimizing errors with proof-reading tiles
  • Counting the glues
  • Sequence design
  • Experiment results

Lecture 3 (2019.11.07):

  • Exercise sessions [ HW3 ]
    1. Making a DNA Origami

Lecture 2 (2019.10.24): Universality in assembly Model (I): Theory and experiment

  • Universality in assembly Model (I) [ Slides ]
    • Simulating a Turing machine at temperature T°=2 in aTAM
    • Optimal hardcoding of a binary string at T°=2 in aTAM
    • Simulating a Turing machine at temperature T°=1 in aTAM in 3D
  • An experimental realisation of a universal computer (I) [ Slides ]
    • Single stranded tile nanotubes
    • Atomic Force Microscopy (AFM)
    • Marking 0s and 1s using biotin-streptavidin
    • kTAM kinetic assembly model
    • Error correction using proof-reading tiles
    • DNA nanotube circuit model
  • Exercise sessions [ HW2 | Solutions ]
    1. Assembly time = O(rank of the produced shape) (from HW1)
    2. Exponential random variables and kTAM implementation
    3. Triangle tile assembly
    4. :!: Tileset for simulating cellular automata (HW2: return your solution by email on or before Thursday Nov 7 at noon)
    5. Probabilistic simulation of Turing Machine at T°=1 in 2D

Lecture 1 (2019.10.17): Introduction to DNA programming & Tile Assembly Systems [ Slides ]

  • Introduction to DNA programming & overview of the field
  • Abstract tile assembly model (aTAM):
    • Definition
    • Minimizing the assembly time
  • Exercise sessions [ HW1 | Solutions ]