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001			233346
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007			cr nn 008mamaa
008			160809s2016 gw | s |||| 0|eng d
020			_a9783662493106
024	7		_a10.1007/978-3-662-49310-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aHydrocarbon and Lipid Microbiology Protocols _bStatistics, Data Analysis, Bioinformatics and Modelling _cedited by Terry J. McGenity, Kenneth N. Timmis, Balbina Nogales Fernández.
250			_a1st edition 2016
264		1	_aBerlin, Heidelberg _bSpringer International Publising _c2016
300			_a1 recurso en línea (XII, 180 páginas) _b
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSpringer Protocols Handbooks _x1949-2456
505	0		_aIntroduction to computer-assisted analysis in lipid and hydrocarbon microbiology -- Application of Ecological Network Theory -- Statistical tools for data analysis -- Statistical tools for study design and replication -- MG-RAST, a metagenomics service for analysis of microbial community structure and function -- Using QIIME to evaluate the microbial communities within hydrocarbon environments -- Biodegradation Prediction Tools -- Predicting protein interactions -- Syntax and Semantics of Coding in Python -- Protocols for calculating reaction kinetics and thermodynamics -- Modelling the environmental fate of hydrocarbons during bioremediation. .
520			_aThis Volume covers protocols for in-silico approaches to hydrocarbon microbiology, including the selection and use of appropriate statistical tools for experimental design replication, data analysis, and computer-assisted approaches to data storage, management and utilisation. The application of algorithms to analyse the composition and function of microbial communities is presented, as are prediction tools for biodegradation and protein interactions. The basics of a major open-source programming language, Python, are explained. Protocols for calculating reaction kinetics and thermodynamics are presented, and modelling the environmental fate of hydrocarbons during bioremediation is explained. With the exception of molecular biology studies of molecular interactions, the use of statistics is absolutely essential for both experimental design and data analysis in microbiological research, and indeed in the biomedical sciences in general. Moreover, studies of highly varying systems call for the modelling and/or application of theoretical frameworks. Thus, while two protocols in this Volume are specific to hydrocarbon microbiology, the others are generic, and as such will be of use to researchers investigating a broad range of topics in microbiology and the biomedical sciences in general. Hydrocarbon and Lipid Microbiology Protocols There are tens of thousands of structurally different hydrocarbons, hydrocarbon derivatives and lipids, and a wide array of these molecules are required for cells to function. The global hydrocarbon cycle, which is largely driven by microorganisms, has a major impact on our environment and climate. Microbes are responsible for cleaning up the environmental pollution caused by the exploitation of hydrocarbon reservoirs and will also be pivotal in reducing our reliance on fossil fuels by providing biofuels, plastics and industrial chemicals. Gaining an understanding of the relevant functions of the wide range of microbes that produce, consume and modify hydrocarbons and related compounds will be key to responding to these challenges. This comprehensive collection of current and emerging protocols will facilitate acquisition of this understanding and exploitation of useful activities of such microbes.
700	1		_aMcGenity, Terry J _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aTimmis, Kenneth N _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aNogales Fernández, Balbina _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783662493090
776	0	8	_iPrinted edition: _z9783662493113
776	0	8	_iPrinted edition: _z9783662570005
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-662-49310-6 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2016
999			_c233346 _d233346