CD Genomics, as one of bioinformatics data analysis providers, we provide services of marker analysis for different biological data. With the advent of personalized medicine and predictive medical diagnosis based on the genetic makeup of patients, more and more researchers have begun to incorporate biomarker analysis into their research categories. In this process, we use bioinformatics methods to help you quickly and accurately analyze and identify candidate biomarkers, thereby saving your costs and accelerating your research.
The concept of biomarkers was first proposed by the National Research Council (NRC) of the United States and is a very hot topic in the medical field. A biomarker generally refers to a certain characteristic biochemical index in a general physiological or pathological or therapeutic process that can provide objective measurement and evaluation. Through its measurement, the current biological process of the body can be learned. With the rise of emerging disciplines such as genomics, proteomics, transcriptomics, metabolomics, and bioinformatics, the research on biomarkers has been promoted. In addition, with the development of personalized medicine and medication, researchers have begun to look for biomolecules that change in the human body as medications or diseases occur.
Biomarkers can not only explore the pathogenesis at the molecular level, but also provide early warning in the early stage of the disease and provide clinicians with a basis for auxiliary diagnosis. At the same time, as a terminal substitute, biomarkers can also help pharmaceutical companies develop more and better targeted drugs. For example, in the medical field, biomarkers can be used for disease diagnosis (for example, prostate-specific antigen PSA is used for the diagnosis of prostate cancer), and to determine the stage of the disease (for example, the stage of tumor), as well as to evaluate the effectiveness and safety of new drugs or new therapies in the target population.
Fig 1. Cytokines involved in COPD. (Barnes P J. 2008)
With the development of sequencing technology, molecular diagnostic technology makes it possible to discover molecular markers, and markers enter the stage of molecular biomarkers. According to the role of biomarkers, it can be divided into three categories.
Biomarkers that can track disease progression and known clinical test-related indicators over time.
Biomarkers for detecting drug effects.
It can be used as an evaluation index for the end point of clinical trials.
Bioinformatics is a subject that combines computer, mathematics, and biology. In the process of biomarker analysis, the genome, transcriptome, proteome, metabolome, epitome sequencing data and chip data are mainly analyzed. Use bioinformatics methods to check, compare and analyze potential biomarkers, and then analyze the regulation of related genes and protein functions. Finally use different prediction models (such as single factor cox + PCA model, Random forest + Artificial neural network models, etc.) screen out biomarkers related to the occurrence and development of diseases or drugs, so as to provide guidance on disease diagnosis and personalized medication.
Fig 2. CD Genomics bioinformatics data analysis process.
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.
Genomic data analysis - CD Genomics provides a full range of genome-wide biological information analysis solutions to help researchers comprehensively analyze all genomes, reveal hidden biomarkers or discover unknown biomarkers.
Transcriptomics data analysis - The analysis of transcriptome data enables researchers to analyze the entire transcriptome of an organism and discover molecular biomarkers related to gene expression, alternative transcription or splicing.
Epigenetics data analysis - In epigenetics, DNA methylation as a potential biomarker is attracting more and more attention. Through the analysis of DNA methylation sequencing data, molecular related sites of methylation-related biomarkers can be mined.
Proteomics Data Analysis - CD Genomics uses bioinformatics methods to perform protein differential expression analysis on proteomics data to find disease-related biomarkers, which is helpful for early diagnosis of disease, post-cure evaluation and new drug development.
Metabolomics Data Analysis - Since metabolomics is the end product of the signal pathway and reflects the physiological state of the body at that time, compared with other omics, metabolomics is closer to the phenotype, so it is more suitable for the discovery and research of markers.
CD Genomics provides a variety of biological information data analysis solutions to help customers complete the research and discovery of biomarkers in different research stages. If you are interested in our services, please contact us for more information and a detailed quote.