Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/24477
Title: | Bioinformatics–the Machine Learning Approach | Authors: | Madevska Bogdanova, Ana | Keywords: | bioinformatics, machine learning, SVM, neural networks | Issue Date: | 2003 | Publisher: | Institute of Informatics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University in Skopje, Macedonia | Conference: | CIIT 2003 | Abstract: | Computational analysis of biological sequences – linear descriptions of protein, DNA and RNA molecules has completely changed its character since the late 1980s. The main driving force behind the changes has been the introduction of new, efficient experimental techniques, primarily DNA sequencing that has led to an exponential growth of data. As genome and other sequencing projects continue to advance, the interest progressively switches from the accumulation of data to its interpretation. There are some problems concerning the vast amount of data in the biological databases that has to be taken into account. | URI: | http://hdl.handle.net/20.500.12188/24477 |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
4CiiT-09.pdf | 222.81 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.