Microbial Science is very wide area for research in biological science. The use of computational genomics and bioinformatics are important tools in this field to reveal the information stored in genetic materials of microorganisms. Microbial genome data is exponentially increasing because of the use of sequencing methods, which presents the microbiology research community with an exciting opportunity and responsibility to assign biological meaning to these data. Computational genomics and bioinformatics bridges data interpretation, technology and software development in the field of microbial science.
Our aim is to encompass significant research findings on aspects of computational genomics and bioinformatics for bacteria, fungi, viruses and archaea. Specifically, the topic aims to include papers that describe computational analysis of evolution of life forms, genomic microbiology as well as computational analysis of nucleotide or amino acid sequences and structures from genomic data. We welcome submissions describing novel methods for Computational Genomics and structural bioinformatics in microbial science in the form of Original Research and Methods papers. Brief Research Reports, Reviews and Perspectives may also be considered.
Specific themes include, but are not limited to
i) Single genome sequences or comparative multiple genomes analysis from pathogens, symbionts, or free-living microbes; Global expression profiles determined at the RNA or protein level;
ii) The results of metagenomic, metatranscriptomic or metaproteomic analysis of both human-associated and environmental niches;
iii) Synthetic genomics and metabolic engineering including systems microbiology;
iv) Advances in genome sequencing approaches relevant to Bacteria, Viruses and Archaea including single-cell methods
v) Genome analysis and characterization of novel coronavirus (2019-nCoV)
vi) New or improved tools for the analysis of microbial genomes, prediction of the function of novel domains, motifs, genes and proteins using omics data related to microbial science
vii) Gut microbiome data analytics
Microbial Science is very wide area for research in biological science. The use of computational genomics and bioinformatics are important tools in this field to reveal the information stored in genetic materials of microorganisms. Microbial genome data is exponentially increasing because of the use of sequencing methods, which presents the microbiology research community with an exciting opportunity and responsibility to assign biological meaning to these data. Computational genomics and bioinformatics bridges data interpretation, technology and software development in the field of microbial science.
Our aim is to encompass significant research findings on aspects of computational genomics and bioinformatics for bacteria, fungi, viruses and archaea. Specifically, the topic aims to include papers that describe computational analysis of evolution of life forms, genomic microbiology as well as computational analysis of nucleotide or amino acid sequences and structures from genomic data. We welcome submissions describing novel methods for Computational Genomics and structural bioinformatics in microbial science in the form of Original Research and Methods papers. Brief Research Reports, Reviews and Perspectives may also be considered.
Specific themes include, but are not limited to
i) Single genome sequences or comparative multiple genomes analysis from pathogens, symbionts, or free-living microbes; Global expression profiles determined at the RNA or protein level;
ii) The results of metagenomic, metatranscriptomic or metaproteomic analysis of both human-associated and environmental niches;
iii) Synthetic genomics and metabolic engineering including systems microbiology;
iv) Advances in genome sequencing approaches relevant to Bacteria, Viruses and Archaea including single-cell methods
v) Genome analysis and characterization of novel coronavirus (2019-nCoV)
vi) New or improved tools for the analysis of microbial genomes, prediction of the function of novel domains, motifs, genes and proteins using omics data related to microbial science
vii) Gut microbiome data analytics
