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Phenomics

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The advent of ‘omics technologies has brought a major paradigm shift towards systematic analysis of biological processes at many different scales. However, the various technologies have not evolved at the same speed due to the different challenges in terms of data acquisition. Genetic approaches have merged ...

The advent of ‘omics technologies has brought a major paradigm shift towards systematic analysis of biological processes at many different scales. However, the various technologies have not evolved at the same speed due to the different challenges in terms of data acquisition. Genetic approaches have merged with genomics to reduce cost and dramatically enhance the efficiency of data acquisition. Thus, a large amount of forward and reverse genetic resources are available (or under rapid construction) for model organisms and an increasing number of crops. Similar advances are occurring for “molecular-level” phenotypes, including the transcriptome, the proteome and the metabolome.

However, acquiring many physical and physiological measurements at similar scales remain a challenge and this is now widely recognised as a limiting factor in exploiting the bonanza of genomic information. “Phenomics “, often used to describe the attempt to address this challenge, is a technology-driven interdisciplinary endeavour where engineering and biology meet to measure individuals and processes in an unbiased and reproducible manner.

Amongst the different phenomic assays under active development is highly parallelised morphometric or physiological analysis of plants, cyanobacteria or algae strains. Automated or high throughput survey systems have been established in very different conditions including highly controlled growth chambers, greenhouses or open field. Alternatively, low numbers of plants or few can be phenotyped in depth.

Both approaches share common technological and informatics challenges with other ‘omics, as well as specific challenges associated with high data dimensionality, temporal and environmental data, metadata standards, ontologies, etc.

For this Research Topic, we welcome manuscripts describing novel methods of phenotyping for cyanobacteria, algae, and land plants (including the identification of mutants, QTLs, or natural variation). We encourage authors to send manuscripts where non-model organisms, crops, or bacteria, algae and higher plants of ecological relevance are measured by automated or semi-automated devices or approaches with the potential to be automated. Examples of software that can extract, or aid the extraction, of biological information or proxies thereof, are particularly encouraged


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