Abstract
Visualization of a large-scale protein databases may help biologists in discovering similarity between sequences of different organisms. In this article we present a complex approach for visually representing relations between proteins in large scale databases. Our approach includes sequence alignment, mutual distance measurement, clustering and classification of protein sequences. We propose a visual representation method for considered as well-established Pfam 4.0 proteins database. Our objective is to visually reflect the similarity of protein sequences in three dimensional space using nonstandard approach.
Keywords
Cite this article
@article{cai-11026,
author = {Patryk Orzechowski and Krzysztof Boryczko},
title = {Parallel Approach for Visual Clustering of Protein Databases},
journal = {Computing and Informatics},
volume = {29},
number = {6+},
pages = {1221--1231},
year = {2010},
issn = {1335-9150},
url = {https://cai.type.sk/content/2010/6%2B/parallel-approach-for-visual-clustering-of-protein-databases/}
}
TY - JOUR AU - Patryk Orzechowski AU - Krzysztof Boryczko TI - Parallel Approach for Visual Clustering of Protein Databases JO - Computing and Informatics VL - 29 IS - 6+ SP - 1221 EP - 1231 PY - 2010 SN - 1335-9150 UR - https://cai.type.sk/content/2010/6%2B/parallel-approach-for-visual-clustering-of-protein-databases/ KW - Clustering algorithms KW - proteins KW - sequence alignment KW - multidimensional scaling ER -
Orzechowski, P., & Boryczko, K. (2010). Parallel Approach for Visual Clustering of Protein Databases. Computing and Informatics, 29(6+), 1221–1231. https://cai.type.sk/content/2010/6%2B/parallel-approach-for-visual-clustering-of-protein-databases/