Bioinformatics Analysis for Endocrinology
The human endocrine system includes the pancreas, thyroid, parathyroid, pineal gland, hypothalamus, adrenal and pituitary glands, ovaries and testes, and also involves many organs that respond to or improve and metabolize hormones. Endocrine disease is a syndrome that occurs when the secretory function and/or structure of the endocrine glands or endocrine tissues themselves are abnormal. It also includes the symptoms of abnormal hormone sources, abnormal hormone receptors, and physiological disorders caused by hormone or substance metabolism disorders. Common endocrine diseases include diabetes, pituitary tumor, hyperlipidemia, thyroiditis and glycogen storage disease, etc.
Application of Bioinformatics in the Research of Endocrinology
In recent years, the diagnosis and treatment of endocrine and metabolic diseases and the molecular mechanisms of pathogenesis have been promoted by basic research in molecular biology development (such as genomics, proteomics, epigenetics, metabolomics, and bioinformatics, etc.). Bioinformatics plays an important role in the process of data analysis, mining and integration. Metabolomics is an emerging discipline that has developed in the context of the vigorous development of systems biology in recent years. Analysis of metabolomics data can reflect the overall metabolic fingerprint, monitor the operating status of the metabolic network in the body, diagnose diseases, evaluate curative effects, and predict the future healthy development trend of the human body. For example, the occurrence and development of diabetes must be accompanied by changes in metabolites, metabolomics technology provides panoramic information for the metabolic status of diabetes, and provides ideas for the realization of its personalized diagnosis and treatment.
Fig 1. Manhattan plots of the sex-combined BMI-unadjusted and adjusted meta-analysis for type 2 diabetes. (Anubha M, et al. 2018)
How We Can Help Your Endocrinology Research
By combining our expertise in bioinformatics analysis with our extensive knowledge in the field of endocrinology, from pre-clinical to clinical, we can provide support for your research at every stage of disease research. Our bioinformatics service can help you with:
- Metabolomics analysis: Draw metabolic fingerprints to assist in monitoring the running status of metabolic networks in the body, diagnosing diseases, and evaluating curative effects.
- Meta-analysis: by integrating phenotypes and environmental or genetic factors, mining factors related to the occurrence of endocrinology diseases.
- Genome-wide association analysis: mining genetic factors related to the occurrence of endocrinology diseases.
- Omics data analysis: Research on the pathogenesis of endocrine system diseases from all aspects.
- Biomarker and target discovery: Identify disease markers and biomarkers used to measure drug efficacy and mechanism of action.
- Build a database: Establish a database related to endocrinology diseases.
In addition, we will use cutting-edge analysis technology to conduct personalized data analysis according to the customer's project analysis needs.
An Example of a Data Analysis Process
CD Genomics provides a one-stop bioinformatics data analysis service, and customers only need to provide raw data. The flowchart below shows the general process of meta-analysis for disease research.
As one of the experienced biological information analysis service providers, CD Genomics provides established, cost-efficient, and rapid turnaround endocrinology data analysis services for biomedical researchers. For endocrinology-related research, CD Genomics not only provides bioinformatics data analysis services, but also helps researchers formulate appropriate technical routes and provide related technical services according to the researchers' research purposes. If you have any questions about the data analysis cycle, analysis content and price, please feel free to click online inquiry.
Biomedical-Bioinformatics, as a division of CD Genomics, not only provides researchers with high-quality personalized data analysis and chart production services, but also provides sequencing and data mining services. We can provide you with a full range of data analysis services to help you save time for wet experimental research. If you have any questions, please feel free to contact us. We have a professional technical support team to provide you with professional answers, and look forward to working with you!
- Anubha M, et al. Fine-mapping of an expanded set of type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps[J]. Nat Genet. Author manuscript; available in PMC 2018 Dec 10.
- Mahajan A, et al. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes[J]. Nature Genetics, 2018, 50(4):559-571.
* For research use only. Not for use in clinical diagnosis or treatment of humans or animals.
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