We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

LONETSSOM Platform: Enabling Distributed Processing, Managing and Mining of Biological Data through Fusion of Logical Network and Web Technologies in NETWORK Infrastructure

by N. Kannaiya Raja, K. Arulandam, A. Senthamaraiselvan, K. Babu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 2
Year of Publication: 2012
Authors: N. Kannaiya Raja, K. Arulandam, A. Senthamaraiselvan, K. Babu
10.5120/4793-7042

N. Kannaiya Raja, K. Arulandam, A. Senthamaraiselvan, K. Babu . LONETSSOM Platform: Enabling Distributed Processing, Managing and Mining of Biological Data through Fusion of Logical Network and Web Technologies in NETWORK Infrastructure. International Journal of Computer Applications. 39, 2 ( February 2012), 23-31. DOI=10.5120/4793-7042

@article{ 10.5120/4793-7042,
author = { N. Kannaiya Raja, K. Arulandam, A. Senthamaraiselvan, K. Babu },
title = { LONETSSOM Platform: Enabling Distributed Processing, Managing and Mining of Biological Data through Fusion of Logical Network and Web Technologies in NETWORK Infrastructure },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 2 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 23-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number2/4793-7042/ },
doi = { 10.5120/4793-7042 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:24.075816+05:30
%A N. Kannaiya Raja
%A K. Arulandam
%A A. Senthamaraiselvan
%A K. Babu
%T LONETSSOM Platform: Enabling Distributed Processing, Managing and Mining of Biological Data through Fusion of Logical Network and Web Technologies in NETWORK Infrastructure
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 2
%P 23-31
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The accurate computation of conventional methods have not relied in the revolutionary period of changes and cannot make reshaping in the biological research as the meta-mining was used for integration of data which is not compatibility for biological research. Therefore we have reshaped the conventional method using Logical Network for effective transcriptomic technology for translation. In this paper, the advanced technology of knowledge mining which have an unprecedented wealth of quantity of data have been sruitnished and we present lonet for in silico systems biology and medicine (LONETSSOM), and a web based application that exploits logical management systems and distributed data processing system are highly used for DNA microarray through a genetic consistent, computational analysis framework. The advanced framework of logical network system is LONETSSOM which perform efficient versatile annotation system and integrative analysis through multi-application programming interface delivered in the SOA. The LONETSSOM aims to setup a generic paradigm of efficient knowledge mining that promotes throughput in translation of biomedicine field through the fusion of logical network and creation of semantic web technologies.

References
  1. D. Janssen. (2006).Managing the microarray data mountain, Bio-IT World. [Online]. Available at: http://www.bio-itworld.com/ BioIT_Article.aspx?id = 41292].
  2. C.Colantuoni, G.Henry, S.Zeger, and J. Pevsner,SNOMAD(standardization and normalization of microarraydata):Web-accessible gene expression data analysis,”Bioinformatics, vol. 18, no. 11, pp. 1540–1541, Nov. 2002.
  3. S. Patel and J. Lyons-Weiler, caGEDA: A web application for the integrated analysis of global gene expression patterns in cancer,” Appl. Bioinfo., vol. 3, no. 1, pp. 49–62, 2004.
  4. H. Rehrauer, S. Zoller, and R. Schlapbach, MAGMA: Analysis of twochannel microarrays made easy,” Nucl. Acid Res., vol. 35, no.Web Server issue, pp. W86–W90, Jul. 2007.
  5. M. Maurer, R. Molidor, A. Sturn, J. Hartler, H. Hackl, G.Stocker, A.Prokesch,M. Scheideler, and Z.Trajanoski, MARS:Microarray analysis, retrieval, and storage system,” BMC Bioinfo vol. 6, art. 101 2005.
  6. J. Tarraga,I.Medina,J.Carbonell,J.Huerta-Cepas,P.Minguez,E.Alloza,F.Al-Shahrour,S. Vegas-Azcarate,S.Goetz,P.Escobar,F.Garcia, A.Conesa, D.Montaner, and J.Dopazo, GEPAS, a web-based tool for microarray data analysis andinterpretation,”Nucl.AcidRes.,vol.36,No.Web Server issue, pp.W308–W314,Jul. 1, 2008.
  7. S. D.Jani, G.L. Argraves, J. L. Barth, and W. S. Argraves,GeneMesh:A web-based microarray analysis tool for relating differentially expressed genes to MeSH terms,”BMC Bioinfo., vol. 11, no. 1, art. 166, Apr. 1, 2010.
  8. I. Kanaris, V. Mylonakis, A. Chatziioannou, I. Maglogiannis, and J. Soldatos, NETWORK: Enabling Microarray Experiments over the HellenicNetworkInfrastructure,”J.Logic network Comput., vol. 7, no. 3, pp. 1–22, Aug. 2009.
  9. I. Porro, L. Torterolo, L. Corradi, M. Fato, A. Papadimitropoulos, S. Scaglione, A. Schenone, and F. Viti,A Network-based solution for management and analysis of microarrays in distributed experiments,” BMC Bioinfo., vol. 8, Suppl. 1, art. S7, 2007.
  10. B. Langmead, K. D. Hansen, and J. T. Leek, Cloud-scale RNAsequencing differential expression analysis with Myrna,”Geno. Bio., vol. 11, art. R83, 2010.
  11. R. C. Gentleman, V. J. Carey, D. M. Bates, B. Bolstad, M. Dettling, S. Dudoit, B. Ellis, L. Gautier, Y.Ge,J. Gentry, K. Hornik, T. Hothorn, W. Huber, S. Iacus, R. Irizarry, F. Leisch, C. Li, M. Maechler, A. J. Rossini, G. Sawitzki, C. Smith, G. Smyth, L. Tierney, J. Y. Yang, and J. Zhang,Bioconductor:Opensoftware Development for computational biology and bioinformatics,” Geno. Bio., vol. 5, no. 10, 2004.
  12. A.Chatziioannou,I.Kanaris, I. Maglogiannis, C.Doukas, P.Moulos,E.Pilalis, and F.N. Kolisis,LONETSSOM web based Network portal: Exploiting the power of Network infrastructure for the interpretation and storage of DNA microarray experiment,” in Proc. IEEE 9th Int. Conf. Inf.Technol. Appl. Biomed. (ITAB),Carnaca,Cyprus, Nov.5–7, 2009, pp. 15.
  13. A. Chatziioannou and P. Moulos, Exploiting statistical methodologies and controlled vocabularies for prioritized functional analysis of genomic experiments: The StRAnGER web application,” Front. Syst. Biol., to be published.
  14. M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler, J.M. Cherry, A. P. Davis, K. Dolinski, S. S. Dwight, J. T. Eppig, M. A. Harris, D. P. Hill, L. Issel-Tarver, A. Kasarskis, S. Lewis, J. C. Matese, J. E. Richardson, M. Ringwald, G. M. Rubin, and G. Sherlock,Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium,” Nat. Gen., vol. 25, no. 1, pp. 25–29, May 2000.
  15. Y. H. Yang, J. Youl Choi, K. Choi, M. Pierce,D.Gannon, and S.Kim,BioVLAB-microarray: Microarray data analysis in virtual environment,” in Proc. IEEE Int. Conf. eSci., 2008, pp. 159–165.
  16. A. Brazma, P. Hingamp, J. Quackenbush, G. Sherlock, P. Spellman, C. Stoeckert, J. Aach,W. Ansorge, C. A. Ball, H. C. Causton, T. Gaasterland, P. Glenisson, F. C. Holstege, I. F. Kim, V. Markowitz, J. C. Matese, H. Parkinson, A. Robinson, U. Sarkans, S. Schulze-Kremer, J. Stewart, R. Taylor, J. Vilo, and M. Vingron, Minimum information about a microarray experiment (MIAME)—Toward standards for microarray data,” Nat. Gen., vol. 29, no. 4, pp. 365–371, Dec. 2001.
  17. R.Edgar and T.Barrett, NCBIGEOstandards and services formicroarray data,” Nat. Biotechnol., vol. 24, no. 12, pp. 1471–1472, Dec. 2006.
  18. A. Chatziioannou, P. Moulos, and F. N. Kolisis, ?Gene ARMADA: An integrated multi-analysis platform for microarray data implemented in MATLAB,” BMC Bioinfo., vol. 10, p. 354, 2009.
  19. A.Tzouvelekis,V.Harokopos,T. aparountas, N. Oikonomou, A. Chatziioannou, G.Vilaras, E. Tsiambas, A. Karameris, D. Bouros, andV. Aidinis, Comparative expression profiling in pulmonary fibrosis suggests a role of hypoxia-inducible factor-1alpha in disease pathogenesis,” Amer. J. Resp. Cri. Car. Med., vol. 176, no. 11, pp. 1108–1119, Dec. 1, 2007.
  20. W. J.Welboren,M. A. Van Driel, E. M. Janssen-Megens, S. J. Van Heeringen, F. C. Sweep, P. N. Span, and H. G. Stunnenberg, ChIP-Seq of ER and RNA polymerase II defines genes differentially responding to ligands,” EMBO J., vol. 28, no. 10, pp. 14181428, 2009.
  21. R. B. Scharpf, C. A. Iacobuzio-Donahue, J. B. Sneddon, and G. Parmigiani, When should one subtract background fluorescence in 2-color microarrays?,” Biostatistics, vol. 8, no. 4, pp. 695–707, Oct. 2007.
  22. R. A. Irizarry, B. Hobbs, F. Collin, Y. D. Beazer-Barclay, K. J. Antonellis, U. Scherf, and T. P. Speed, Exploration, normalization, and summaries of high density oligonucleotide array probe level data,” Biostatistics, vol. 4,no. 2, pp. 249–264, Apr. 2003.
  23. G. C. Tseng, M. K. Oh, L. Rohlin, J. C. Liao, and W. H. Wong, Issues in cDNA microarray analysis: Quality filtering, channel normalization, models of variations and assessment of gene effects,” Nucl. Acid Res., vol. 29, no. 12, pp. 2549–2557, Jun. 15, 2001.
  24. B. M.Bolstad, R.A.Irizarry,M. Astrand, and T. P. Speed, A comparison of normalization methods for high density oligonucleotide array data based on variance and bias,” Bioinformatics, vol. 19, no. 2, pp. 185–193, Jan. 22, 2003.
  25. J.W.Tukey, Exploratory Data Analysis. Reading MA: Addison-Wesley, 1977.
  26. C.R.Pelz, M.Kulesz-Martin, G. Bagby, and R.C.Sears,Global rankinvariant set normalization (GRSN) to reduce systematic distortions in microarray data,” BMC Bioinfo., vol. 9, art. 520, 2008.
  27. G. Casella, and R. L.Berger. Statistical inference. 2nd edition. Belmont, CA: Duxbury Press, 2002.
  28. K. Pruitt, T. Tatusov, and D. Maglott. .RefSeq and LocusLink: NCBI gene-cantered resources. Nucleic Acids Res., vol. 29, pp. 137-140, 2001.
  29. B. Boeckmann, A. Bairoch, R. Apweiler, M. C. Blatter, A. Estreicher, and E. Gasteiger. .The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res., vol. 31, pp. 365-370, 2003.
  30. M. Kanehisa, and S. Goto. .KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acid Res., vol. 28, no. 1, pp. 27-30, 2000.
  31. V. A. McKusick. Mendelian Inheritance in Man. A catalog of human genes and genetic disorders. 12th edition. Baltimore, MD: Johns Hopkins University Press, Johns Hopkins University Press, 1998.
  32. K. Moutselos, I.Kanaris, A. Chatziioannou, and F. N. Kolisis, KEGGconverter:BMC Bioinfo., vol. 10, art. 324, 2009.
  33. E.Newcomer and G.Lomow, Understanding SOA with Web Services.Reading, MA: Addison-Wesley, 2004.
  34. T. Oinn, M. Addis, J. Ferris, D. Marvin, M. Senger, M. Greenwood, T. Carver, K. Glover, M. R. Pocock, A. Wipat, and P. Li, Taverna: A tool for the composition and enactment of bioinformatics workflows,” Bioinformatics, vol. 20, no. 17, pp. 3045–3054, Nov. 22, 2004.
  35. K. Gabhart. (2007). Secure, Reliable Web Services with IIS Web Server.
  36. The OpenSSL Project. (2002). [Online]. Available at: http://www.openssl.org/.
Index Terms

Computer Science
Information Sciences

Keywords

DNA microarray Data set Data Preprocessing Statistical Analysis Clustering Annotation Interpretation WSDL knowledge-mining.

Powered by PhDFocusTM