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Ontological Tools in Anaerobic Fermentation Technologies: Bioinformation Database Applications

An important direction of forming an effective system for recycling waste of various genesis is to optimize the processes of their treatment using the latest information resources. The paper deals with theoretical studies of directions for the systematization and optimization of anaerobic waste processing technologies using ontological tools based on information resources. Significant scientific support to biochemical research is provided by electronic bioinformatics databases such as KEGG, BacDive, and EAWAG-BBD, etc., which provide access to a collection of graphical representations and text descriptions of metabolic or signal pathways, schemes of regulation of biological processes, information about the organism. They cover various aspects of bacterial and archaic biodiversity, information on microbial biocatalytic reactions and biodegradation pathways of mainly xenobiotic chemical compounds. Also, in the course of work based on analytical data of electronic databases of bioinformatics, in particular, the interaction of necessary ecological and trophic groups of microorganisms, biochemical simulation of anaerobic waste processing with biofuel production was carried out. Keywords: waste disposal, bioinformatics database, anaerobic fermentation, biofuel.
- Hokkaido Bunkyo University Japan
- Hokkaido Bunkyo University Japan
- Sumy State University Ukraine
- Sumy State University Ukraine
anaerobic fermentation, waste disposal, bioinformatics database, Engineering (General). Civil engineering (General), biofuel, TA1-2040
anaerobic fermentation, waste disposal, bioinformatics database, Engineering (General). Civil engineering (General), biofuel, TA1-2040
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).2 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
