Defining the pathogenesis of inflammatory and immune diseases through database mining.
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.
Temple University School of Medicine, Philadelphia, PA 19140, USA. fannibal@gmail.com
Fan
F
Yang
Irene Hwa
IH
Yang
Daniel H
DH
Chen
D017398:Alternative Splicing; D020170:Caspase 1 / Q000378:metabolism; D016208:Databases, Factual; D004789:Enzyme Activation; D000939:Epitopes / Q000276:immunology; D006801:Humans; D007154:Immune System Diseases / Q000209:etiology*; D007249:Inflammation / Q000209:etiology*; D016247:Information Storage and Retrieval
D000939:Epitopes; D020170:Caspase 1