The revolutionary growth in computation speed and memory storage capability has fueled a new era in analysing biological data. Rapid progress has been made in the techniques and equipment of high-throughput technologies (sequencing, omics), enabling an exponentially growing knowledge acquisition of microbial genomes and microbiome. Advances in genome sequencing technologies and metagenomic analysis have enabled researchers to study these microbes and their function and research microbiome-based interactions in the natural and industrial environment through human health and agricultural systems. However, the vast amount of information generated in these ways has to be stored, structured, indexed, analyzed, and tied up to available experimental data. This need has resulted in the development of bioinformatics at the intersection of microbiology and information science.
We created a research topic to fill a gap for which no publication avenue is particularly geared to computationally oriented, strongly biologically motivated, and pragmatic articles focused on microbes. On the one hand, the bioinformatics journals are generally very computer technical and unlikely to be read by the diverse community of microbiologists. There is also a strong emphasis in bioinformatics literature on human/mammalian systems, though this is a secondary issue. On the other hand, microbial informatics work has appeared in a variety of microbiological publications. Still, it is seldom a good fit, and methods that span diverse microbes have no obvious home.
This Research Topic aims to collect all article types (Original Research papers, critical Reviews focusing on recent achievements in this field and short Perspectives) related to microbiome and microbial informatics. Specific topics may include but are not limited to the microbiome, microbial comparative genomics, microbial protein structure and function, microbial systems and metagenomics, the mathematical modelling of microbial systems. We would be happy to consider it if you have worked at the interface between computation and microbiology (both broadly defined).
The revolutionary growth in computation speed and memory storage capability has fueled a new era in analysing biological data. Rapid progress has been made in the techniques and equipment of high-throughput technologies (sequencing, omics), enabling an exponentially growing knowledge acquisition of microbial genomes and microbiome. Advances in genome sequencing technologies and metagenomic analysis have enabled researchers to study these microbes and their function and research microbiome-based interactions in the natural and industrial environment through human health and agricultural systems. However, the vast amount of information generated in these ways has to be stored, structured, indexed, analyzed, and tied up to available experimental data. This need has resulted in the development of bioinformatics at the intersection of microbiology and information science.
We created a research topic to fill a gap for which no publication avenue is particularly geared to computationally oriented, strongly biologically motivated, and pragmatic articles focused on microbes. On the one hand, the bioinformatics journals are generally very computer technical and unlikely to be read by the diverse community of microbiologists. There is also a strong emphasis in bioinformatics literature on human/mammalian systems, though this is a secondary issue. On the other hand, microbial informatics work has appeared in a variety of microbiological publications. Still, it is seldom a good fit, and methods that span diverse microbes have no obvious home.
This Research Topic aims to collect all article types (Original Research papers, critical Reviews focusing on recent achievements in this field and short Perspectives) related to microbiome and microbial informatics. Specific topics may include but are not limited to the microbiome, microbial comparative genomics, microbial protein structure and function, microbial systems and metagenomics, the mathematical modelling of microbial systems. We would be happy to consider it if you have worked at the interface between computation and microbiology (both broadly defined).