Neural networks in the analysis of nucleotide genomic signals

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dc.contributor.authorCristea, Paul Dan
dc.date.accessioned2024-07-12T20:56:16Z
dc.date.available2024-07-12T20:56:16Z
dc.date.issued2009en_US
dc.departmentMaltepe Üniversitesi, İnsan ve Toplum Bilimleri Fakültesien_US
dc.description.abstractConverting nucleotide sequences to digital signals [1] allows to apply signal processing methods for the analysis of genomic data. The method reveals surprising regularities in the distribution of nucleotides, pairs of nucleotides and small groups of nucleotides along a chromosome, in both prokaryotes and eukaryotes. These features of nucleotide sequences would be difficult to find by using only symbolic genomic sequences and standard statistical and pattern matching methods [2]. The mapping we have used in our work [1, 3] is a one-to-one unbiased representation of nucleotide equivalence classes, which attaches quadrantal complex numbers to adenine, cytosine, guanine and thymine nucleotides.en_US
dc.identifier.citationCristea, P. D. (2009). Neural networks in the analysis of nucleotide genomic signals. Maltepe Üniversitesi. s. 325-326.en_US
dc.identifier.endpage326en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage325en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2948
dc.institutionauthorCristea, Paul Dan
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07672
dc.titleNeural networks in the analysis of nucleotide genomic signalsen_US
dc.typeConference Object
dspace.entity.typePublication

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