Vishwakarma et al.

conclusion

In case of high-throughput EST analysis there is a need for integrated, automated

approaches enabling EST data mining for the biologically useful information

across disciplinary boundaries. Moreover, ESTs have diverse applications, and the

question being addressed will determine the choice of methods or pipelines to be

used. As the objective of individual methods and tools can vary substantially, it

is difficult to evaluate all of them using a common platform and choose the most

appropriate ones for individual projects.

As the data is limited forABC transporters genes expressed in human, identification

of ESTs from various tissue sources need to be identified (Sutcliffe et al., 1982).

The correlation is needed now to investigate the difference between the nucleotide/

protein sequences which ultimately results in its absolute function. The BLAST

and alignment results have shown not much significant differences in all identified

sequences.

While complete genomes are the ultimate data sets for resolving phylogenetic and

evolutionary issues of different kinds, the production of human brain ESTs for

ABC transporters are still at a level that precludes a dense taxonomic sampling

among higher organisms. Therefore, there is need to establish methods that can

be used to predict the sequence homology and of general interest for phylogenetic

studies. Production and investigation of new ESTs from various tissue sources in

human and other higher eukaryotes will gain more attention in future.

References

Adams MD, Kelley JM, Gocayne JD, et al., 1991. “Complementary DNA sequencing:

expressed sequence tags and human genome project”. Science., 252 (5013): 1651–

1656.

Campagne F, Skrabanek L 2006. “Mining expressed sequence tags identifies cancer

markers of clinical interest”. BMC Bioinformatics., 7 : 481.

Christoffels A, van Gelder A, Greyling G, Miller R, Hide T, Hide W 2001. “STACK:

Sequence Tag Alignment and Consensus Knowledgebase”. Nucleic Acids Res., 29 (1):

234–238.

Nagaraj SH, Gasser RB, Ranganathan S 2007. “A hitchhiker’s guide to expressed sequence

tag (EST) analysis”. Brief. Bioinformatics., 8 (1): 6–21.

Skrabanek L, Campagne F 2001. “TissueInfo: high-throughput identification of tissue

expression profiles and specificity”. Nucleic Acids Res., 29 (21): E102–2.

Sutcliffe JG, Milner RJ, Bloom FE, Lerner RA 1982. “Common 82-nucleotide sequence

unique to brain RNA”. Proc Natl Acad Sci U S A., 79 (16): 4942–4946.

12

Int. J. Bioinformatics and Biological Sci.: v.2 n.1&2, p. 7-12. March & June 2014