1Departments of Rheumatology and Medicine, Hospital for Joint Diseases, New York, NY 10003, USA
2Departments of Pathology and Medicine, New York University School of Medicine, New York, NY 10016, USA
3Kaplan Cancer Center, New York, NY 10016
4Molecular Medicine Laboratories, Yamanouchi Pharmaceutical Co. Ltd., Tsukuba, Ibaraki, Japan
*Corresponding author: Rheumatology Research and Laboratory for Functional Genomics, Hospital for Joint Diseases/ NYU School of Medicine, 301 East 17th Street, Rm. 1600, New York, NY 10003, USA
Human and other annotated genome sequences have facilitated generation of vast amounts of correlative data, from human/animal genetics, normal and disease-affected tissues from complex diseases such as arthritis using gene/protein chips and SNP analysis. These data sets include genes/proteins whose functions are partially known at the cellular level or may be completely unknown (e.g. ESTs). Thus, genomic research has transformed molecular biology from "data poor" to "data rich" science, allowing further division into subpopulations of subcellular fractions, which are often given an "-omic" suffix. These disciplines have to converge at a systemic level to examine the structure and dynamics of cellular and organismal function.
The challenge of characterizing ESTs linked to complex diseases is like interpreting sharp images on a blurred background and therefore requires a multi-dimensional screen for functional genomics ("functionomics") in tissues, mice and zebra fish model, which intertwines various approaches and readouts to study development and homeostasis of a system. In summary, the post-genomic era of functionomics will facilitate to narrow the bridge between correlative data and causative data by quaint hypothesis-driven research using a system approach integrating "intercoms" of interacting and interdependent disciplines forming a unified whole as described in this review for Arthritis.
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