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|a Microbial metagenomics in effluent treatment plant
|h [electronic resource] /
|c edited by Maulin P. Shah.
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|a [S.l.] :
|b Elsevier,
|c 2024.
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|a 1 online resource.
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|a References -- 3 Response of microbial community to environment changes -- 3.1 Introduction -- 3.1.1 Elevated CO2 -- 3.2 Effect of drought on soil microbes drought -- 3.3 Alpha diversity of microbes in carbon, nitrogen, and phosphorous cycle -- 3.4 Effect of excess rain and water on soil microbes -- 3.5 Different communities of soil microbes -- 3.6 Rise in temperature -- 3.7 Microbes in the soil and the rising incidence of fires -- 3.8 Biochemical properties of soil -- 3.9 Effect of microbes on gaseous exchange -- 3.10 Adapting to climate change through soil microbiome manipulation.
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|a Front Cover -- Microbial Metagenomics in Effluent Treatment Plant -- Copyright Page -- Contents -- List of contributors -- 1 Polycyclic aromatic hydrocarbon degradation by bacterial communities: a sustainable approach -- 1.1 Introduction -- 1.2 Genetics of polycyclic aromatic hydrocarbon-degrading bacteria -- 1.3 Conclusion and future perspectives -- References -- 2 Analysis of complex microbial communities in soil and wastewater treatment processes -- 2.1 Introduction -- 2.1.1 Anaerobic digestion and composting.
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|a 2.2 Value of researching microbial communities in waste-transformation procedures -- 2.3 Cooccurrence network analysis for the characterization of microbial communities -- 2.3.1 Antibiotic resistance gene and microbial genotoxin detection by metagenomics in a natural setting -- 2.3.2 Antibiotics are being filtered out of wastewater -- 2.3.3 Toxic byproduct -- 2.4 Research aimed toward Phylogenetic Fingerprinting of the Whole Communities -- 2.4.1 Wastewater treatment plant microbiological diversity -- 2.4.2 The microbial mechanism for metal tolerance -- 2.5 Conclusion -- List of abbreviations.
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|a 3.10.1 Carbon cycle and soil microbes -- 3.10.2 Effect of biotic factors on soil rhizosphere -- 3.11 Recent developments in molecular methods for analyzing the soil microbiome -- 3.12 Changes in plant-microbe interaction caused by global warming -- 3.13 Case study: drought impacts on microbial communities in both minimally and heavily managed grassland -- 3.14 Case study microorganism -- 3.14.1 Heavy rainfall -- 3.15 Conclusion -- Abbreviations -- References -- 4 Gene prediction through metagenomics -- 4.1 Introduction -- 4.2 Genomics versus metagenomics.
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|a 4.3 Gene prediction in Eukaryotes versus prokaryotes -- 4.4 Significance of metagenomics -- 4.5 Methods of gene prediction -- 4.6 Models and algorithms -- 4.7 MetaGUN for metagenomic fragments based on a machine learning approach of support vector machine -- 4.7.1 Architecture of MetaGUN algorithm -- 4.8 Glimmer -- 4.9 Algorithm structure -- 4.10 Ab initio gene identification in metagenomic sequences -- 4.11 Heuristic system of model parameters derivation -- 4.12 Orphelia -- 4.12.1 Metaprodigal -- 4.12.2 MGC -- 4.13 Metageneannotator -- 4.14 Predictions on short genomic sequences.
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