Abstract
High Content Screening (HCS) and High Content Analysis (HCA) have emerged over the past 10 years as a powerful technology for both drug discovery and systems biology. Founded on the automated, quantitative image analysis of fluorescently labeled cells or engineered cell lines, HCS provides unparalleled levels of multi-parameter data on cellular events and is being widely adopted, with great benefits, in many aspects of life science from gaining a better understanding of disease processes, through better models of toxicity, to generating systems views of cellular processes. This paper looks at the role of informatics and bioinformatics in both enabling and driving HCS to further our understanding of both the genome and the cellome and looks into the future to see where such deep knowledge could take us.
Highlights
Completed in 2003, the Human Genome Project (HGP) resulted in the sequencing of the 30,000 genes contained in the entire human genome [1], while this was a remarkable effort, we are only at the beginning of our understanding of the role of all these genes in living systems
Functional genomics, the role of genes in complex traits and disease, gene regulation and complex systems biology are just some of the questions that were raised by the HGP and are the subject of much research
In the same manner that genomics solved the problem of high throughput data acquisition but hit a bottleneck with respect to infrastructure and tools to manage and mine that data for knowledge, so High Content Screening (HCS) is reaching the same status
Summary
Completed in 2003, the Human Genome Project (HGP) resulted in the sequencing of the 30,000 genes contained in the entire human genome [1], while this was a remarkable effort, we are only at the beginning of our understanding of the role of all these genes in living systems. Functional genomics, the role of genes in complex traits and disease, gene regulation and complex systems biology are just some of the questions that were raised by the HGP and are the subject of much research. HCS systems typically scan a multi-well plate with cells or cellular components in each well, acquire multiple images of cells, and extract multiple features (or measurements) relevant to the biology, resulting in a large quantity of data and images. While the management of this kind of data is becoming commonplace, tools to generate ‘omic knowledge from billions of cellular measurements are less mature and we believe may hinder HCS from achieving its full potential of solving the cellome. We look to the future to see how computational modeling and simulation could impact our insight of the cellome
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