Bioinformatics Analysis for Clinical Research

Bioinformatics Analysis for Clinical Research

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Bioinformatics-Analysis, a division of CD Genomics, provides bioinformatics services related to every stage of clinical research. We provide you with one-stop clinical data and database bioinformatics solutions, so you can focus on the real business. For data analysis, you only need to provide the original data, and we will provide standardized and personalized analysis of disease data. For database construction, we can build a database for structured patient information management, homogenized clinical data analysis, multi-center collaborative analysis, and personalized expansion analysis according to your needs. So as to help clinicians manage patient information, carry out data mining and explore scientific research ideas.

Introduction of Clinical Research

Since the 21st century, biomedicine has gradually entered the era of big data. For example, massive sequencing data represented by genomes, transcriptomes, and proteomes, as well as microarray data, will provide an unprecedented opportunity for profoundly revealing the mechanism of human diseases and finding therapeutic drugs. In addition, with the establishment of various medical databases and platforms, it provides doctors with real-time online case and data management, as well as visualized clinical decision-making auxiliary information and other services, greatly improving the work efficiency of clinicians.

Bioinformatics is a science that studies biological information processing-collection, management and analysis applications, and extracts new biological knowledge from it. It connects biological data and medical scientific research. In clinical data research, bioinformatics is often applied to data analysis in various aspects such as disease genomics, disease evolution and heterogeneity, early disease detection and diagnosis, and genetic risk research. In addition, with the accumulation of data, various clinical-related biological information databases have emerged. Currently, bioinformatics covers almost all fields of life sciences.

Fig 2. Progression of disease over time by cluster. Fig 1. Progression of disease over time by cluster. (Ahlqvist E, et al. 2018)

Bioinformatics in Clinical Research

Through bioinformatics methods, combining clinical data and existing database information, such as genome database, nucleic acid and protein database, biological macromolecule three-dimensional spatial structure database and some other secondary databases, search for pathogens or human disease-related genetic information. Design specific primers and probes through biological software for clinical gene diagnosis, typing, quantification, and identification of drug resistance genes. It plays an important role in the prevention, early diagnosis, treatment, and prognosis of infectious diseases, genetic diseases, and tumors. In this process, even if you don't have the original data, we can mine the existing data in the database for relevant analysis according to your needs. In short, you only need to provide the original clinical data or analysis requirements, and we will provide you with complete data analysis services.

Fig 3. CD Genomics bioinformatics data analysis process. - CD Genomics. Fig 2. CD Genomics bioinformatics data analysis process.

What can CD Genomics Do?

We can assist in your clinical research at every stage by offering our proprietary bioinformatics analysis approaches, including sequencing data and microarray data analysis and database construction. In clinical research, CD Genomics offers a comprehensive analysis approach for augmenting clinical trial outcomes, ensuring you get the most information out of your research.

Genomics data analysis, transcriptomics data analysis, - Through the analysis of SNP mutation sites, the disease mutation spectrum is constructed, and the association analysis between clinical phenotype and genotype is performed. Through the cluster analysis of clinical features and molecular tags, disease classification is performed.

Whole Genome Bisulfite Methylation, Exosomal RNA Sequencing Analysis,- Through the analysis of biomarkers, early detection of diseases such as tumors.

Database Construction - Construct multi-dimensional digital disease information from genetics, mutations, immunity, infection, etc., integrate gene mutation information, clinical interpretation information, clinical diagnosis and treatment information, and follow-up information to provide a disease database for later data mining.

CD Genomics has extensive project experience in clinical data analysis and clinical database construction, covering different types of diseases. Regarding data analysis and clinical database construction services, we can customize different service content according to your needs. For clinical data analysis services, if you have any questions, please feel free to contact us for details.


  1. Ahlqvist E, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables[J]. Lancet Diabetes Endocrinol, 2018:S2213858718300512.

* For Research Use Only. Not for use in diagnostic procedures.
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