Name
Title | ||
|---|---|---|
Subcellular Localisation of Proteins in Living Cells Using a Genetic Algorithm and an Incremental Neural Network |
Abstract | ||
|---|---|---|
The subcellular localisation of proteins in living cells is a crucial means for the determination of their function. We propose an approach to realise such a protein localisation based on microscope im- ages. In order to reach this goal, appropriate features are selected. Then, the initial feature set is optimised by a genetic algorithm. The actual classiflcation of possible protein localisations is accomplished by an in- cremental neural network which not only achieves a very high accuracy, but enables on-line learning, as well. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-71091-2_3 | Bildverarbeitung für die Medizin |
Keywords | Field | DocType |
neural network,genetic algorithm | Protein localisation,Biology,Feature set,Artificial intelligence,Artificial neural network,Genetic algorithm,Machine learning | Conference |
Citations | PageRank | References |
2 | 0.40 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marko Tscherepanow | 1 | 150 | 10.53 |
| Franz Kummert | 2 | 103 | 20.41 |