Image and fractal information processing for large-scale chemoinformatics, genomics analyses and pattern discovery

Authors:
Ilkka Havukkala;Lubica Benuskova;Shaoning Pang;Vishal Jain;Rene Kroon;Nikola Kasabov
Affiliations:
Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand;Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand
Venue:
PRIB'06 Proceedings of the 2006 international conference on Pattern Recognition in Bioinformatics
Year:
2006

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Abstract

Two promising approaches for handling large-scale biodata are presented and illustrated in several new contexts: molecular structure bitmap image processing for chemoinformatics, and fractal visualization methods for genome analyses. It is suggested that two-dimensional structure databases of bioactive molecules (e.g. proteins, drugs, folded RNAs), transformed to bitmap image databases, can be analysed by a variety of image processing methods, with an example of human microRNA folded 2D structures processed by Gabor filter. Another compact and efficient visualization method is comparison of huge amounts of genomic and proteomic data through fractal representation, with an example of analyzing oligomer frequencies in a bacterial phytoplasma genome. Bitmap visualization of bioinformatics data seems promising for complex parallel pattern discovery and large-scale genome comparisons, as powerful modern image processing methods can be applied to the 2D images.