000			06197nam a2200697 i 4500
001			6812638
003			IEEE
005			20200413152902.0
006			m eo d
007			cr cn |||m|||a
008			110617s2011 caua foab 000 0 eng d
020			_a9781608451463 (electronic bk.)
020			_z9781608451456 (pbk.)
024	7		_a10.2200/S00360ED1V01Y201105BME041 _2doi
035			_a(CaBNVSL)gtp00548364
035			_a(OCoLC)742535641
040			_aCaBNVSL _cCaBNVSL _dCaBNVSL
050		4	_aQH324.2 _b.N253 2011
082	0	4	_a572.80285 _222
100	1		_aNalbantoglu, Ozkan Ufuk.
245	1	0	_aComputational genomic signatures _h[electronic resource] / _cOzkan Ufuk Nalbantoglu and Khalid Sayood.
260			_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool, _cc2011.
300			_a1 electronic text (xii, 113 p.) : _bill., digital file.
490	1		_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v# 41
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
500			_aPart of: Synthesis digital library of engineering and computer science.
500			_aSeries from website.
504			_aIncludes bibliographical references (p. 85-112).
505	0		_a1. Genome signatures, definition and background -- Definition of computational genomic signatures -- Compositional features as genome signatures -- GC content -- Amino acid content -- Synonymous Codon usage -- Methods of characterization embedded in the initial work on DNA -- Dinucleotide odds ratio as a genome signature -- Chaos game representation -- A unified framework of genome signatures: functions of oligonucleotide -- Occurrence -- Natural selection of proteins vs. directional mutational pressures --
505	8		_a2. Other computational characterizations as genome signatures -- Long-term correlation statistics as genome signatures -- DNA as an autoregressive process -- Average mutual information profiles -- Signatures based on composition vectors -- Markov models -- Abundance profiles of oligonucleotides -- Oligonucleotide frequency derived error gradient (OFDEG) -- DNA entropy -- Methods of estimating DNA entropy -- Historical notes on biological complexity and DNA entropy -- Correlation of DNA entropy with OFDEG signatures --
505	8		_a3. Measuring distance of biological sequences using genome signatures -- Classical methods: euclidian distances and correlation statistics -- Distances based on model fitness -- Likelihood functions -- Indexing based on oligonucleotide abundance -- Minimum description length calculation based on linguistic models --
505	8		_a4. Applications: phylogeny construction -- A half century of molecular phylogenetics and the need for universal methods -- Phylogenetic signals in genome signatures -- Phylogeny with information theoretic distance measures and implicit genome signatures -- Phylogeny construction by genome signatures using genomic fragments -- Drawbacks of genome-signature-based phylogeny construction --
505	8		_a5. Applications: metagenomics -- Community analysis of environmental samples -- Sampling and sequencing environmental samples -- Exploration of biodiversity in a metagenome -- Metagenome assembly -- Metagenome binning -- Similarity search-based binning methods -- Supervised compositional binning methods -- Unsupervised methods --
505	8		_a6. Applications: horizontal DNA transfer detection -- Horizontal gene transfer -- Horizontal gene transfer in prokaryotes -- Horizontal gene transfer in eukaryotes -- Horizontal gene transfer detection -- Comparative methods -- Methods based on genome signatures -- Performance and limitations of genome signatures for horizontal transfer detection -- Compositional similarity of host and donor genomes -- Other challenges limiting the performance of genome-signature-based horizontal transfer detection -- Amelioration and deviation from general genomic signature trends --
505	8		_aBibliography -- Authors' biography.
506	1		_aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510	0		_aCompendex
510	0		_aINSPEC
510	0		_aGoogle scholar
510	0		_aGoogle book search
520	3		_aRecent advances in development of sequencing technology has resulted in a deluge of genomic data. In order to make sense of this data, there is an urgent need for algorithms for data processing and quantitative reasoning. An emerging in silico approach, called computational genomic signatures, addresses this need by representing global species-specific features of genomes using simple mathematical models. This text introduces the general concept of computational genomic signatures, and it reviews some of the DNA sequence models which can be used as computational genomic signatures. The text takes the position that a practical computational genomic signature consists of both a model and a measure for computing the distance or similarity between models. Therefore, a discussion of sequence similarity/distance measurement in the context of computational genomic signatures is presented. The remainder of the text covers various applications of computational genomic signatures in the areas of metagenomics, phylogenetics and the detection of horizontal gene transfer.
530			_aAlso available in print.
588			_aTitle from PDF t.p. (viewed on June 17, 2011).
650		0	_aBioinformatics.
650		0	_aGenomics.
653			_aGenome
653			_aMarkov models
653			_aMinimum description length
653			_aKolmogorov complexity
653			_aPhylogeny
653			_aClassification
653			_aHorizontal gene transfer
653			_aMetagenomics
653			_aBioinformatics
700	1		_aSayood, Khalid.
776	0	8	_iPrint version: _z9781608451456
830		0	_aSynthesis digital library of engineering and computer science.
830		0	_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v# 41.
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6812638
999			_c561850 _d561850