[Frontiers in Bioscience E4, 2433-2441, June 1, 2012]

Defining the pathogenesis of inflammatory and immune diseases through database mining

Fan Yang1, Irene Hwa Yang1, Daniel H. Chen1

1Temple University School of Medicine, Philadelphia, PA, 19140

TABLE OF CONTENTS

1. Abstract
2. Introduction
3. What are the principles of database mining?
4. Example 1: stimulation-responsive alternative splicing is an important mechanism in generating self-antigen epitopes
5. Example 2: a three tier model for caspase-1 activation and inflammation privilege are important mechanisms underlying the differences in the inflammation initiation in tissues
6. Example 3: anti-inflammatory microRNAs may play critical roles in inhibiting the expression of pro-atherogenic molecules
7. Conclusion
8. Acknowledgements
9. References

1. ABSTRACT

Recent research in human and animal genomes, transcriptomes, proteomes, and antigen-omes has generated a large library of data and has led to the establishment of many experimental data-based searchable databases. Scientists now face new, unprecedented challenges to develop more systemic methods to analyze experimental data and generate new hypotheses. This review will briefly summarize our pioneering efforts in using new database mining methods to answer important questions in inflammatory and immune-related diseases. The new principles and basic methodologies of database mining developed in Dr. Yang's laboratory will be delineated in the following studies: 1) a stimulation-responsive alternative splicing model for generating untolerized autoantigen epitopes; 2) a three-tier model for caspase-1 activation and inflammation privileges of various organs; and 3) a group of anti-inflammatory microRNAs which inhibit proatherogenic gene expression during atherogenesis. With technological advances, database mining has provided important insight into new directions for experimental research.