CISC 449
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Basic DNA Computing by David Wood
Abbreviated Table of Contents
- Preface
- I. Background on DNA Computing, Biology, and Computer Science
- Introduction to DNA Computing
- An Example DNA Computation
- What Problems are Suited to DNA Computing?
- Present Interplay of Biology and Computer Science
- Computer Science Applied to Biology
- Computer Science Inspired by Biology
- Computer Science Borrows from Biology
- II. DNA Computing Encroaches on Biology, Computer Science, and Computer Algebra
- DNA Computing Takes a Byte of Biology
- Properties of DNA
- Enzymes and Their Error Rates
- Laboratory Techniques From Biology and Their Error Rates
- DNA Computing Takes a Bite of Computer Science
- Conceptual Overview Of P And NP
- Background: Complexity Bounds
- Problems: Decisions, Inventories, And Optima
- Problems In P Are Easy To Solve
- NP Problems Are Easy To Check
- NP-Complete: Equivalent Hard Problems In NP
- NP-Hard: More Than Just Decisions
- Some Bad News About NP Approximation
- DNA as a computing Medium
- Enhancing Computation With Biological Supplements
- Implementing Nondeterministic Algorithms
- Bites of NP-Complete via DNA Computing
- Inventing DNA Computing: The Hamiltonian Path Problem, HPP
- Generality for DNA Computing: The 3-Satisfiability Problem, 3-SAT
- Scaling Up DNA Computing: The Traveling Salesman Problem, TSP
- DNA Computing Bites into Computer Algebra: Where the Hard Problems Are
- It's Combinatorics that Makes Problems Hard
- A Ladder of Complexity
- Expansion Of A Symbolic Determinant Given Its Zero Pattern, ESD0
- III. Toward Practical DNA Computers
- DNA Computer Engineering
- How to Show a DNA Computer Works
- Encoding Data in DNA for Associative Annealing
- DNA Memory and Data Structures
- Intra-Computer Communication
- DNA Computer Architectures
- DNA Computer Instruction Set
- Input and Output
- DNA/Silicon Hybrid Computers
- References
David H Wood / / Last revised October 9, 1997