fenómica

Fenómica, or phenomics, is the systematic study of the phenome, the set of all observable traits of an organism, under genetic and environmental variation, with a focus on large-scale, high-throughput measurement to link genotype to phenotype.

It relies on high-throughput phenotyping platforms such as automated imaging, robotics, sensors, and field and greenhouse phenotyping setups. Data are collected across developmental stages and environmental conditions, and described using standardized ontologies. It integrates with genomics, transcriptomics, proteomics, and other omics, and uses statistical genetics, genome-wide association studies, and phenome-wide association studies to map genotype–phenotype relationships.

Applications span plant and animal research and extend to medicine and ecology. In agriculture, phenomics supports crop improvement and trait discovery; in biomedicine, it contributes to biomarker identification and precision medicine; in ecology and evolution, it enables deep phenotyping of populations and species under varying environments.

Challenges include managing large, heterogeneous datasets; achieving data standardization and interoperability; ensuring reproducibility; addressing privacy concerns in human data; and developing robust methods to extract meaningful phenotypes from images and sensor streams. Ongoing efforts emphasize data standards, FAIR data principles, and the integration of phenotypic data with other omics to enable systems-level understanding.

The term phenomics describes the large-scale, systematic study of phenotypes and their relationships to genetics and environment, a field that has grown in prominence with advances in high-throughput measurement technologies and data science since the late 20th century.