Significance of bioinformatics in research of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction [1,2]. It can be caused by inflammatory responses triggered by noxious particles or gas, most commonly from tobacco smoking and is accompanied by chronic bronchitis and emphysema [3,4]. Some patients go on to require long-term oxygen therapy or even lung transplantation [3]. COPD was ranked as fourth leading cause of death worldwide and is estimated to become the top third cause of mortality by 2020 [5]. According to the data in China, COPD ranks as the fourth leading cause of death in urban areas and third in rural areas[6]. The high mortality and morbidity with COPD, and its chronic progressive nature, have promoted the need to investigate the underlying mechanisms and identify biomarkers for diagnosis, prognosis and drug target.The understanding of COPD increased by advanced molecular biology approaches, genetically modified animals, virally administered genes, and high-throughput transcriptional profiling approaches. High-throughput methodologies, such as genomics and proteomics, are commonly used. The variety of data from biology, mainly in the form of DNA, RNA and protein sequences is putting heavy demand in computer sciences and computational biology. Bioinformatics, including many sub-disciplines, such as genomics, proteomics and system biology, is an integration of mathematical, statistical, and computational methods to analyze biological, biochemical, and biophysical data. Compared to wet-lab method, bioinformatics focused on data mining via computational means. Sophisticated bioinformatics techniques are developed to analyze the vast amount of data generated from genomics and proteomics studies, such as gene and protein function, interactions and metabolic and regulatory pathways. However, there is still a great challenge to combine the computer figures with clinical data for both be