# 20581 Biological Computation

**Credits: **4 advanced credits in Computer Science

**Prerequisites**: Students must fulfill all **English** requirements and take **bibliographic instruction** in the Library.

Required: Introduction to Statistics and Probability for Science Students (or Probability for Computer Science Students); Data Structures and Introduction to Algorithms (or Data Structures); Differential and Integral Calculus I (or Infinitesimal Calculus I); Linear Algebra I (or Linear Algebra for Natural Science Students)

Recommended: Automata Theory and Formal Languages, Introduction to the Theory of Computation and Complexity,1 Algorithmics: The Foundations of Computer Science, Algorithms and Introduction to Life Sciences (or General Biology I and General Biology II)

The course is based on a reader edited by Ron Unger and Ehud Lamm.

The course surveys four topics at the crossroads of Biology and Computer Science: Cellular automata, molecular computing, evolutionary computation, and neural networks. Common to all four is the ability of these simple models to describe complex behavior or to solve a difficult problem (for example, NP-complete problems).

It demonstrates how ideas from the field of Biology can contribute to dealing with difficult computation problems and how ideas from Computer Science can contribute to understanding biological processes and mechanisms. Within this context, the course focuses on questions worthy of empirical and theoretical research.

1or **Computational Complexity** (20545) or **Computability and Introduction to Complexity** (20365), which are no longer offered.