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The data mining of microsatellites markers from EST data can be a cost effective option.
Because of its negligible cost, in silico mining of microsatellites makes this approach more comfortable than bench screening of genomic libraries.
in silico mining of microsatellites repeats may provide a useful basis for carrying out further investigation of its structural and functional characteristics.
A Leishmania Microsatellite Database (LeishMicrosatDB) is reported for genome wise mining of microsatellites in six Leishmania species, using in silico techniques.
EuMicroSat db (Eukaryotic MicroSatellite d ata b ase) is a web based relational database for easy and efficient positional mining of microsatellites from sequenced eukaryotic genomes.
The recent availability of huge amount of sequence data for a wide range of organisms, together with new methodological developments of in silico mining of microsatellites, have tremendously increased the characterization of these markers [ 5], and will certainly catalyze the study of genomic distribution of microsatellites in eukaryotes.
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As compared to other methods, bioinformatics mining of microsatellite markers from EST datasets is one of the most efficient and economical way.
We attempted to circumvent this problem by bioinformatic mining of microsatellite sequences from a de novo-sequenced transcriptome of a butterfly (Euphydryas editha).
These sequence resources available in the public domain have also served as an attractive source of in silico mining of microsatellite sequences [ 1- 5].
EuMicrosat db has been developed for genome wide mining of microsatellite in 31 completely sequenced eukaryotic genomes considering the immense utility of these sequences for a variety of experiments.
The LeishMicrosatDB allows mining of different microsatellites along with their physical location in the chromosomes in six fully sequenced Leishmania species.
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