Secondary Structure Libraries for Artificial Evolution Experiments

Graphical Evolution Experiments in Artificial Life

Population Structure and Artificial Evolution

We investigate the effect that population structure has upon the course of artificial evolution. We represent an arbitrary population structure by embedding a population of individuals in a graph. Each individual resides at a vertex of the graph and can only choose a mating partner from among its neighbors in the graph. Each individual mates with the selected partner and is replaced by the resu...

Using Artificial Neural Network for Protein Secondary Structure prediction

Some properties of a protein can be determined from Knowing the secondary structure of the protein. The known structure of proteins so far was done using a technique called X-ray diffraction patterns of crystallized then the data from the process is fed through the DSSP algorithm(Kabsch and Sander, 1983) to determine the exact protein structure. The process is time consuming and expensive. Ther...

Artificial Neural Network Method for Predicting Protein Secondary Structure Content

In this paper, the neural network method was applied to predict the content of protein secondary structure elements that was based on 'pair-coupled amino acid composition', in which the sequence coupling effects are explicitly included through a series of conditional probability elements. The prediction was examined by a self-consistency test and an independent-dataset. Both indicated good resu...

How to Do Experiments in Artificial Language Evolution and Why

The paper discusses methodological issues for developing computer simulations, analytic models , or experiments in artificial language evolution. It examines a few examples, evaluation criteria, and conclusions that can be drawn from such efforts.