About: Genome Signatures, Self-Organizing Maps and Higher Order Phylogenies: A Parametric Analysis

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About: Genome Signatures, Self-Organizing Maps and Higher Order Phylogenies: A Parametric Analysis Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Genome Signatures, Self-Organizing Maps and Higher Order Phylogenies: A Parametric Analysis
Creator	Gatherer, Derek
Source	Medline; PMC
abstract	Genome signatures are data vectors derived from the compositional statistics of DNA. The self-organizing map (SOM) is a neural network method for the conceptualisation of relationships within complex data, such as genome signatures. The various parameters of the SOM training phase are investigated for their effect on the accuracy of the resulting output map. It is concluded that larger SOMs, as well as taking longer to train, are less sensitive in phylogenetic classification of unknown DNA sequences. However, where a classification can be made, a larger SOM is more accurate. Increasing the number of iterations in the training phase of the SOM only slightly increases accuracy, without improving sensitivity. The optimal length of the DNA sequence k-mer from which the genome signature should be derived is 4 or 5, but shorter values are almost as effective. In general, these results indicate that small, rapidly trained SOMs are generally as good as larger, longer trained ones for the analysis of genome signatures. These results may also be more generally applicable to the use of SOMs for other complex data sets, such as microarray data.
has issue date	2007-09-17(xsd:dateTime)
bibo:pmid	19468314
has license	cc-by
sha1sum (hex)	d3b9423ca41bdd129766dce07506a87b9eec22a7
resource representing a document's title	Genome Signatures, Self-Organizing Maps and Higher Order Phylogenies: A Parametric Analysis
has PubMed Central identifier	PMC2684143
has PubMed identifier	19468314
schema:publication	Evol Bioinform Online
resource representing a document's body	covid:d3b9423ca41bdd129766dce07506a87b9eec22a7#body_text
is schema:about of	named entity 'CORRESPONDENCE' named entity 'SELF' named entity 'IMPROVING' named entity 'VALUES' named entity 'DNA SEQUENCES' named entity 'ACCURACY' named entity 'NUMBER OF ITERATIONS' named entity 'SENSITIVE' named entity 'NEURAL NETWORK' named entity 'PARAMETERS' named entity 'INCREASING' named entity 'SMALL' named entity 'COMPLEX' named entity 'RESULTING' named entity 'RELATIONSHIPS' named entity 'CONCEPTUALISATION' named entity 'APPLICABLE' named entity 'MAP' named entity 'VARIOUS' named entity 'AS GOOD' named entity 'OPTIMAL' named entity 'EFFECTIVE' named entity 'ANALYSIS' named entity 'SIGNATURES' named entity 'SOM' named entity 'MER' named entity 'SIGNATURE' named entity 'METHOD' named entity 'VECTORS' named entity 'LARGER' named entity 'ACCURATE' named entity 'IS A' named entity 'SENSITIVITY' named entity 'DATA SETS' named entity 'EFFECT' named entity 'SELF-ORGANIZING MAP' named entity 'UNKNOWN' named entity 'OUTPUT' named entity 'ORDER' named entity 'GENOME' named entity 'TRAIN' named entity 'PARAMETRIC ANALYSIS' named entity 'SIGNATURES' named entity 'THESE' named entity 'DERIVED' named entity 'DATA' named entity 'STATISTICS' named entity 'INCREASES' named entity 'PHASE' named entity 'GENERAL' named entity 'INVESTIGATED' named entity 'MICROARRAY DATA' named entity 'GENOME' named entity 'THEIR' named entity 'HIGHER' named entity 'TAKING' named entity 'SLIGHTLY' named entity 'CATION' named entity 'USE OF' named entity 'LENGTH' named entity 'ORGANIZING' named entity 'MAPS' named entity 'BUT' named entity 'RAPIDLY' named entity 'ALMOST' named entity 'TRAINING' named entity 'DNA SEQUENCE' named entity 'DNA' named entity 'TRAINED' named entity 'RESULTS' named entity 'WHERE' covid:arg/d3b9423ca41bdd129766dce07506a87b9eec22a7 named entity 'GS-2' named entity 'genomes' named entity 'neural network' named entity 'Biochemical studies' named entity 'vector' named entity 'GS-2' named entity 'viral genomes' named entity 'bioinformatics' named entity 'SOM' named entity 'SOMs' named entity 'Genome'

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