About this Research Topic
Next generation sequencing has revolutionized biological research. However, as the number of sequences in databases increases exponentially, it is becoming increasingly clear that the path connecting the genotype to the phenotype is far from being a straight one. This is true when single organisms are considered and, especially, when studying a group of interacting cells (community).
To fill this gap and to analyze and put genomic information in a broader context, computational models are often used. These include, for example, statistical models used in large-scale comparative metagenomics studies and mathematical dynamic models to predict microbial communities fluctuations. Additionally, specific cellular information layers can be modeled and investigated, as in the case of cellular metabolism with the advent of constraint-based metabolic modeling or gene regulatory circuits with the use of probabilistic boolean networks and/or differential equation based models.
The importance of modeling cellular and community-level features is becoming a crucial issue in systems biology. In this context, computational modeling and in silico simulations are flourishing, applied to metabolic engineering of microbial strains, to human disease and also to the whole microbiome and host-microbiome interactions.
The aim of the Research Topic “From sequence to models” is to stimulate a debate and promote a platform for dissemination of the computational methods, challenges, and solutions devoted to functional modelling of DNA sequence data coming from genomic and metagenomic studies.
Keywords: genomics, metagenomics, metabolism, constraint based modelling, Flux Balance Analysis, statistical modes, regression models
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