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Journal of Biosciences
Article . 2002 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Comparative genomics using data mining tools

Authors: Tannistha, Nandi; Chandrika, B-Rao; Srinivasan, Ramachandran;

Comparative genomics using data mining tools

Abstract

We have analysed the genomes of representatives of three kingdoms of life, namely, archaea, eubacteria and eukaryota using data mining tools based on compositional analyses of the protein sequences. The representatives chosen in this analysis were Methanococcus jannaschii, Haemophilus influenzae and Saccharomyces cerevisiae. We have identified the common and different features between the three genomes in the protein evolution patterns. M. jannaschii has been seen to have a greater number of proteins with more charged amino acids whereas S. cerevisiae has been observed to have a greater number of hydrophilic proteins. Despite the differences in intrinsic compositional characteristics between the proteins from the different genomes we have also identified certain common characteristics. We have carried out exploratory Principal Component Analysis of the multivariate data on the proteins of each organism in an effort to classify the proteins into clusters. Interestingly, we found that most of the proteins in each organism cluster closely together, but there are a few 'outliers'. We focus on the outliers for the functional investigations, which may aid in revealing any unique features of the biology of the respective organisms

Keywords

Saccharomyces cerevisiae Proteins, Archaeal Proteins, Methanococcus, Computational Biology, Genomics, Saccharomyces cerevisiae, Sequence Analysis, DNA, Haemophilus influenzae, Bacterial Proteins, Genome, Archaeal, Humans, Genome, Fungal, Genome, Bacterial

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
gold