Bioinformatics Analysis for Hematology

Introduction

Hematological diseases refer to diseases that originate in the hematopoietic system, or affect the hematopoietic system with abnormal blood changes, and are characterized by anemia, bleeding, and fever. The hematopoietic system includes blood, bone marrow mononuclear-macrophage system and lymphoid tissues. All diseases that involve the pathology and physiology of the hematopoietic system and whose main manifestations belong to the category of hematological diseases. At present, there are many factors that cause hematological diseases, such as: chemical factors, physical factors, biological factors, heredity, immunity, pollution, etc., which can become the inducement or direct cause of the onset of hematological diseases. Common blood diseases include leukemia, thalassemia, megaloblastic anemia and so on.

Application of Bioinformatics in the Research of Hematology

Bioinformatics is a discipline formed with the integration of human genome life sciences, information sciences, and multiple disciplines since the 1980s. In recent years, with the advancement of genome projects and sequencing technologies, massive amounts of sequencing data related to blood diseases have been generated. Using bioinformatics methods to fully excavate and utilize genomic data provides a new opportunity for the improvement of the diagnosis and treatment of blood diseases. For example, the analysis of the characteristics of the disease genome has deepened the understanding of the biological molecular mechanisms of hematological diseases. Through the analysis of molecular targets and biomarkers, new targets for drug resistance related to hematological diseases have been discovered. Bioinformatics technology plays an important role in the research process of blood diseases.

Fig 1. JAK/STAT-MYC and metabolic signatures in ANKL patients. The bar plot shows the mRNA expression level of MYC in ANKL patients and healthy donors. (Huang L, et al. 2018)

How We Can Help Your Hematology Research

By combining our expertise in bioinformatics analysis with our extensive knowledge in the field of hematology, from pre-clinical to clinical, we can support your disease research at every stage. Our bioinformatics service can help you with:

• Genome-wide association analysis: mining genetic factors related to the occurrence of hematological diseases.
• Meta-analysis: by integrating phenotypes and environmental or genetic factors, mining factors related to the occurrence of hematological diseases.
• Omics data analysis: Research on the pathogenesis of hematological diseases.
• Biomarker and target discovery: Identify disease markers and biomarkers used to measure drug efficacy and mechanism of action.
• Genotyping analysis: SNP genotype analysis and DNA sequence analysis are used to detect new SNPs related to disease or drug response.
• Data landscaping and mining: Data landscaping and mining of public datasets.
• Establish a database related to hematological 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 genome-wide association analysis for disease research.

Service Process

As one of the experienced bioinformatics analysis service providers, CD Genomics provides established, cost-efficient, and rapid turnaround hematology data analysis services for biomedical researchers. For hematology-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.

What's More

Biomedical-Bioinformatics, as a division of CD Genomics, provides researchers with high-quality personalized data analysis and chart production services. For hematology research, we 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 we look forward to working with you!

References

1. Li Y, et al. Human NOTCH4 is a key target of RUNX1 in megakaryocytic differentiation[J]. Blood, 2018,131(2):191-201.
2. Huang L, et al. Integrated genomic analysis identifies deregulated JAK/STAT-MYC-biosynthesis axis in aggressive NK-cell leukemia[J]. Cell Res. 2018 Feb;28(2):172-186.

* For research use only. Not for use in clinical diagnosis or treatment of humans or animals.