{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T14:54:06Z","timestamp":1770476046813,"version":"3.49.0"},"reference-count":37,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2018,6,18]],"date-time":"2018-06-18T00:00:00Z","timestamp":1529280000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2018,8,26]]},"abstract":"<jats:p>Consensus is a significant part that supports the identification of unknown information about animals, plants and insects around the globe. It represents a small part of Deoxyribonucleic acid (DNA) known as the DNA segment that carries all the information for investigation and verification. However, excessive datasets are the major challenges to mine the accurate meaning of the experiments. The datasets are increasing exponentially in ever seconds. In the present article, a memory saving consensus finding approach is organized. The principal component analysis (PCA) and independent component (ICA) are used to pre-process the training datasets. A comparison is carried out between these approaches with the Apriori algorithm. Furthermore, the push down automat (PDA) is applied for superior memory utilization. It iteratively frees the memory for storing targeted consensus by removing all the datasets that are not matched with the consensus. Afterward, the Apriori algorithm selects the desired consensus from limited values that are stored by the PDA. Finally, the Gauss-Seidel method is used to verify the consensus mathematically.<\/jats:p>","DOI":"10.3233\/jifs-169695","type":"journal-article","created":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T15:03:35Z","timestamp":1529420615000},"page":"1555-1565","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Big DNA datasets analysis under push down automata"],"prefix":"10.1177","volume":"35","author":[{"given":"Md. S.","family":"Kamal","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, East West University Bangladesh, Bangladesh"}]},{"given":"Munesh C.","family":"Trivdedi","sequence":"additional","affiliation":[{"name":"Department of Information Technology and Engineering, REC, Azamgarh, UP, India"}]},{"given":"Jannat B.","family":"Alam","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, East West University Bangladesh, Bangladesh"}]},{"given":"Nilanjan","family":"Dey","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Techno India College of Technology, West Bengal, India"}]},{"given":"Amira S.","family":"Ashour","sequence":"additional","affiliation":[{"name":"Department of Electronics and Electrical Communications Engineering, Faculty of Engineering,  Tanta University, Egypt"}]},{"given":"Fuqian","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Information and Engineering, Wenzhou Medical University, Wenzhou, PR China"}]},{"given":"Jo\u00e3o Manuel R.S.","family":"Tavares","sequence":"additional","affiliation":[{"name":"Instituto de Ci\u00eancia e Inova\u00e7\u00e3o em Engenharia Mec\u00e2nica e Engenharia Industrial, Departamento de Engenharia Mec\u00e2nica, Faculdade de Engenharia, Universidade do Porto, Portugal"}]}],"member":"179","published-online":{"date-parts":[[2018,6,18]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2015.2388448"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2015.2476790"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2015.2474389"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2015.2452916"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2015.04.002"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.11.086"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.11.088"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.03.039"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2015.07.061"},{"key":"e_1_3_1_11_2","unstructured":"http:\/\/www.chemguide.co.uk\/organicprops\/aminoacids\/doublehelix.gif."},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720016420026"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720015420056"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720015500262"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbi.2005.04.003"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.2174\/1574893611666151231185112"},{"key":"e_1_3_1_17_2","first-page":"42","article-title":"Collapsible pushdown automata and recursion schemes","author":"Hague M.","year":"2017","unstructured":"HagueM., MurawskiA.S., OngC.H.L. and SerreO., Collapsible pushdown automata and recursion schemes, ACM Trans Comput Logic (2017), 42.","journal-title":"ACM Trans Comput Logic"},{"key":"e_1_3_1_18_2","first-page":"81","article-title":"The Dfam database of repetitive DNA families","volume":"2015","author":"Hubley R.","unstructured":"HubleyR. and FinnR.D., The Dfam database of repetitive DNA families, Nucleic Acid Researchs2015, 81\u201389.","journal-title":"Nucleic Acid Researchs"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/2949033"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-8-S5-S5"},{"key":"e_1_3_1_21_2","article-title":"A method for generating new datasets based on copy number for cancer analysis","author":"Kim S.","year":"2015","unstructured":"KimS., ConM. and KangH., A method for generating new datasets based on copy number for cancer analysis, BioMed Research Int (2015).","journal-title":"BioMed Research Int"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003440"},{"key":"e_1_3_1_23_2","article-title":"a simple tool to parse, manipulate and search large datasets of sequences,","author":"Sobhy Shetti H.","year":"2015","unstructured":"Sobhy ShettiH., a simple tool to parse, manipulate and search large datasets of sequences,, Microbial Genomics (2015).","journal-title":"Microbial Genomics"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm463"},{"key":"e_1_3_1_25_2","first-page":"1089","article-title":"Microarray analysis of autoimmune diseases by machine learning procedures","author":"Arnedillo A.","year":"2009","unstructured":"ArnedilloA., MolinosR.C., CanoB.I., HoyosI.L., TaboadaM.M., UcarV., BernalesE, FullaondoI., M\u00fagicaA.L., ZubiagaP. and Mar\u00edaA., Microarray analysis of autoimmune diseases by machine learning procedures, IEEE Transactions on Information Technology in Biomedicine (2009), ISSN 1089\u20137771.","journal-title":"IEEE Transactions on Information Technology in Biomedicine"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1093\/dnares\/dsw007"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btt300"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1005994"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkw593"},{"key":"e_1_3_1_30_2","unstructured":"ItJ. Principal Component analysis (1986) New York: Springer."},{"key":"e_1_3_1_31_2","unstructured":"JohnsonR.A. and WichernD.W. Applied multivariate statistical analysis (2001) Upper Saddle River NJ: Prentice Hall."},{"key":"e_1_3_1_32_2","first-page":"559","article-title":"On lines and planes of closest fit to systems of points in space","author":"Pearson K.","year":"1901","unstructured":"PearsonK., On lines and planes of closest fit to systems of points in space, Philosophical Magazine (1901), 559\u2013572.","journal-title":"Philosophical Magazine"},{"key":"e_1_3_1_33_2","unstructured":"BishopC. Pattern recognition and machine learning (2006) Springer-Verlag."},{"key":"e_1_3_1_34_2","unstructured":"HaykinS.S. Modern filters (1989 Macmillan."},{"key":"e_1_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-7439(98)00031-8"},{"key":"e_1_3_1_36_2","first-page":"745","article-title":"Cluster analysis of the elderly at home: A case study","author":"Jolliffe I.T.","year":"1980","unstructured":"JolliffeI.T., JonesB. and MorganB.J.T., Cluster analysis of the elderly at home: A case study, Data Anal. Inform (1980), 745\u2013757.","journal-title":"Data Anal. Inform"},{"key":"e_1_3_1_37_2","unstructured":"KnudsenS. Cancer diagnostics with DNA Microarrays. (2006) Hoboken NJ: John Wiley and Sons."},{"key":"e_1_3_1_38_2","doi-asserted-by":"crossref","unstructured":"McLachlanG.J. and AmbroiseD.K.A.C. Analyzing microarray gene expression data (2004) Wiley Interscience.","DOI":"10.1002\/047172842X"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-169695","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-169695","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-169695","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T19:28:12Z","timestamp":1770406092000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-169695"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,18]]},"references-count":37,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,8,26]]}},"alternative-id":["10.3233\/JIFS-169695"],"URL":"https:\/\/doi.org\/10.3233\/jifs-169695","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,18]]}}}