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Computational approaches to phenotyping: high-throughput phenomics.

Yves A Lussier¹, Yang Liu

¹Section of Genetic Medicine, Department of Medicine, University of Chicago,Chicago, Illinois 60637, USA. lussier@uchicago.edu

Proceedings of the American Thoracic Society

|January 5, 2007

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High-throughput phenotyping (HTP) advances systems biology by linking genotypes to phenotypes. This research uses computational tools to build networks for understanding disease at a molecular level.

Area of Science:

Genomics
Systems Biology
Bioinformatics

Background:

The Human Genome Project enables a systems approach to understanding human diseases.
Phenotypic alterations are key indicators of gene function changes, but systematic analysis is nascent.
High-throughput phenotyping (HTP) is an emerging field.

Purpose of the Study:

To review technological advancements in high-throughput phenotyping (HTP) research.
To highlight the potential of computational approaches in phenomics.
To discuss the derivation of genomewide genotype-phenotype associations.

Main Methods:

Leveraging high-throughput computation and informatics.
Developing novel tools for managing large-scale phenotypic databases.

Related Experiment Videos

Integrating and organizing cross-species phenotypic data.

Main Results:

Genomewide molecular networks of genotype-phenotype associations can be derived.
Computational approaches are powerful for large-scale phenomics studies.
Technological advancements are critical for HTP research.

Conclusions:

HTP phenomics research aims to accelerate disease elucidation and treatment strategies.
The field requires significant technological development in computation and informatics.
Linking genomic data with phenotypic information is crucial for understanding biology at multiple scales.