Bioinformatics Analysis for Oncology
Cancer is the most common cause of death in clinical patients. It occurs in multiple organs in a certain system of the body, multiple systems in a certain organ, or a complex disease that coexists with these two conditions. Tumors are divided into benign tumors and malignant tumors. The malignant tumor is often referred to as cancer. Cancer is a disease caused by some genetic changes and epigenetic changes. In its simplest form, cancer is a genetic disease caused by changes in the genome of a cell. Such genetic changes include point mutations, insertion mutations, deletion mutations and chromosomal translocations. Changes in these genes can lead to abnormal cell and tissue growth, which is the phenotypic characteristic of tumors.
Application of Bioinformatics in Tumor Research
Tumor is a disease in which DNA mutations continue to accumulate, leading to an uncontrolled surge in cells and the formation of new organisms. With the development of sequencing technology and the arrival of the post-genome era, molecular biologists can study tumor DNA (genome), mRNA (transcriptome) and protein sequence (proteome) more comprehensively and finely. Through bioinformatics analysis, the main goal is to combine the analysis of various omics to identify new proto-oncogenes or tumor suppressor genes to provide new methods for tumor diagnosis, tumor clinical outcome prediction, and tumor target treatment. For example, tumor cells have various DNA mutations. Through bioinformatics analysis, it is also an important research work to find out which genes play a key role in the early stages of tumor formation and development. Finding mutations in these genes will be the most critical step in future cancer diagnosis and treatment.
Fig 1. Bioinformatics methods are used to analyze the expression profile of polarity complex genes in human cancer. (Lin W H, et al. 2015)
How We Can Help Your Oncology Research
By combining our expertise in bioinformatics analysis with our extensive knowledge in the field of oncology, we can support your research at every stage of drug development from preclinical to clinical. Our bioinformatics service can help with:
- SNP genotype analysis and DNA sequence analysis are used to detect new SNPs related to disease or drug response.
- Biomarker identification: identification of biomarkers used to measure drug efficacy and mechanism of action
- Combine multi-omics (such as genome, transcriptome, proteome, metabolome) to study the mechanism of disease occurrence.
- Predicting biomarkers for classification/stratification of patient response to drug.
- Target identification and validation.
Our customized solutions utilize the most advanced methods and are tailored to the data types and needs of each project.
Advantages of CD Genomics
- CD Genomics provides a one-stop bioinformatics data analysis service, customers only need to provide raw data.
- A team of data analysis experts with rich experience in oncology projects.
- Accurate, efficient, and repeatable analysis results.
- Complete and easy-to-understand final report.
- Provide data downloading service and sequencing service.
If you have any questions about the data analysis cycle, analysis content and price, please click online inquiry.
Biomedical-Bioinformatics, as a division of CD Genomics, provides established, cost-efficient, and rapid turnaround tumor data analysis services for biomedical researchers or doctors. For tumor-related research, CD Genomics not only provides bioinformatics data analysis services, but can also help researchers formulate appropriate technical routes and provide related technical services according to the research purposes of the researchers, from experiments to sequencing to data analysis. As one of the experienced biological information analysis service providers, CD Genomic provides researchers with high-quality personalized data analysis and chart production services. For more detailed information, such as sequencing or data analysis services and other chart production services, please feel free to contact us.
- Lin W H, et al. Expression of polarity genes in human cancer[J]. Cancer informatics, 2015, 14(Suppl 3):15-28.
- Kaissi O, et al. Genes Selection Comparative Study in Microarray Data Analysis[J]. Bioinformation, 2013, 9(20):1019-1022.
* For research use only. Not for use in clinical diagnosis or treatment of humans or animals.
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