Hydrocarbon and Lipid Microbiology Protocols: Statistics, Data Analysis, Bioinformatics and Modelling (Springer Protocols Handbooks)

This 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.

This 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.