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Significance of bioinformatics in research of chronic obstructive pulmonary disease.

Chen H, Wang X - J Clin Bioinforma (2011)

Bottom Line: Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world.The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies.We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China. xiangdong.wang@telia.com.

ABSTRACT
Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world. The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies. As an interdispline, bioinformatics supplied vital information on integrative understanding of COPD. This review focused on application of bioinformatics in COPD study, including biomarkers searching and systems biology. We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians.

No MeSH data available.


Related in: MedlinePlus

Overview of the utility of bioinformatics in chronic obstructive pulmonary disease. Both genomics and proteomics provide information on candidates. By searching in various datasets and combining with clinical profiles, 'omis' studies may help to explain questions on disease classification, biomarker detection, and identification of mechanism.
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Figure 1: Overview of the utility of bioinformatics in chronic obstructive pulmonary disease. Both genomics and proteomics provide information on candidates. By searching in various datasets and combining with clinical profiles, 'omis' studies may help to explain questions on disease classification, biomarker detection, and identification of mechanism.

Mentions: Proteomics is the systematic study of the many and diverse properties of protein profiles in a parallel manner with the aim of providing detailed descriptions of the structure, function and control of biological systems in health and disease [25]. A major research objective is to search for biomarkers in complex biological fluids. The proteomic analysis highlights the avenues to investigate protein profiles of cells, biopsies and fluids, explore protein-based mechanisms of human diseases, define subgroups of disease, and identify novel biomarkers for diagnosis, therapy and prognosis of multiple diseases and discover new targets for drug development. In particular, the application of complementary approaches, including gel- and liquid chromatography mass spectrometry-based proteomic techniques on sputum and/or bronchoalveolar lavage may provide a better understanding of the proteome differentially expressed among the courses, severities and populations of COPD [7]. We have previously reviewed the clinical studies on COPD proteomics, highlighted the proteomic-oriented methods applied and evaluated the diagnostic or prognostic values of potential biomarkers [8]. Those studies mainly focused on disease classification, biomarker detection, or identification of mechanism, while the three components are related with each other in COPD (Figure 1).


Significance of bioinformatics in research of chronic obstructive pulmonary disease.

Chen H, Wang X - J Clin Bioinforma (2011)

Overview of the utility of bioinformatics in chronic obstructive pulmonary disease. Both genomics and proteomics provide information on candidates. By searching in various datasets and combining with clinical profiles, 'omis' studies may help to explain questions on disease classification, biomarker detection, and identification of mechanism.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3285039&req=5

Figure 1: Overview of the utility of bioinformatics in chronic obstructive pulmonary disease. Both genomics and proteomics provide information on candidates. By searching in various datasets and combining with clinical profiles, 'omis' studies may help to explain questions on disease classification, biomarker detection, and identification of mechanism.
Mentions: Proteomics is the systematic study of the many and diverse properties of protein profiles in a parallel manner with the aim of providing detailed descriptions of the structure, function and control of biological systems in health and disease [25]. A major research objective is to search for biomarkers in complex biological fluids. The proteomic analysis highlights the avenues to investigate protein profiles of cells, biopsies and fluids, explore protein-based mechanisms of human diseases, define subgroups of disease, and identify novel biomarkers for diagnosis, therapy and prognosis of multiple diseases and discover new targets for drug development. In particular, the application of complementary approaches, including gel- and liquid chromatography mass spectrometry-based proteomic techniques on sputum and/or bronchoalveolar lavage may provide a better understanding of the proteome differentially expressed among the courses, severities and populations of COPD [7]. We have previously reviewed the clinical studies on COPD proteomics, highlighted the proteomic-oriented methods applied and evaluated the diagnostic or prognostic values of potential biomarkers [8]. Those studies mainly focused on disease classification, biomarker detection, or identification of mechanism, while the three components are related with each other in COPD (Figure 1).

Bottom Line: Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world.The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies.We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China. xiangdong.wang@telia.com.

ABSTRACT
Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world. The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies. As an interdispline, bioinformatics supplied vital information on integrative understanding of COPD. This review focused on application of bioinformatics in COPD study, including biomarkers searching and systems biology. We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians.

No MeSH data available.


Related in: MedlinePlus