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Random-model of simulated evolution


392163 Marília Braga, Nils Hoffmann, Jens Stoye, Roland WittlerSummer 2009 Dates: see below ekvv
Date, time, placeTopic
16.04., 9:15, U10-155 Preliminaries
20.04., 18:15, U10-146 Journal Club 1: Rose (Eyla)
27.04., 18:15, U10-146 Journal Club 2: DAWG (Kai), Strope et al. (Stefan)
04.05., 18:15, U10-146 Journal Club 3: Varadarajan et al. (Christoph), Ma et al. (Madis)
06.05., 17:30, U10-146 Discussion on topics
12.05., 10:15, U10-146 Further discussions
19.05., 17:15, U10-146 specification & architecture
28.05., 17:15, U10-146 For now last group meeting, Further meetings in subgroups
04.06., 17:15, U10-146 SHORT-Meeting
15.06., 17:15, U10-146 yet another Rose Meeting
01.09., 10:15, U10-155 status-update meeting
08.09., 13:15, U10-155 status-update meeting
15.09., 13:15, U10-155 status-update meeting
24.09., 11:00, U10-155 status-update meeting

Milestones

MILESTONE: Funktion nur gültig, wenn JUnit Test vorliegt!!

MilestoneDateTopic
0 sofort Use Cases, Projektprozent
I 2.10. Inputs in Rose Data, Mock Object, Use Cases im Wiki
II 9.10. Probe Durchlauf (Mock), spez. output
III16.10. Output visualisierung, annotation klopfen
IV 23.10. Feature-stop, Doku konzept
V 30.10. ALLES FERTIG

* Alpha Status 0: Use Cases

Project Sections

SVN URL: http://svn.cebitec.uni-bielefeld.de/svn/aggiprojects/rose/

:!: Build Server URL: http://dev.dany2k.de/build :!:

Official Announcement

This project is about the simulation of evolution.

Based on Darwin's fundamental observations we have the following general scheme:

  1. The individual organisms in a population vary in some random way.
  2. They overproduce (if the available resources allow).
  3. Natural selection favors the reproduction of those individuals that are best adapted to the environment.
  4. Some of the variations are inherited to the offspring.

Here, an individual may be represented by its DNA or protein sequence, its genome, or any other collection of characteristic data items, even bitmaps showing some type of animals are conceivable. The production of new individuals may happen by random events, through recombination with other individuals (a.k.a. sex), or a combination of both. A fitness function determines which individuals will form the next generation.

The goal of this project is to write a software that simulates this scheme through the definition of individuals, species, mutational operators, fitness functions, and a control structure working on top of all this. The resulting tool may be used to create data sets for the experimental assessment of multiple sequence alignment, genomic distance, and phylogenetic tree reconstruction algorithms. Technically, the implementation will be done in Java, following a modular, service-oriented software architecture. The user interface shall be graphical, and a visual output is desired.

An extension of the project may be the implementation of a game where the goal of the players is to define individuals with properties such that they produce a maximum amount of offspring in the course of evolution. Obviously, many particular instances of such a game are possible …

Prerequisites: Knowledge of Java programming, basic insights in evolutionary processes.

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