Biological Network Analysis

SPEAK TO A SCIENTIST

With many years of data analysis experience, CD Genomics provides you with various types of biological network analysis services, including biological networks between proteins, genes, RNA, DNA and metabolites, aiming to help you discover the interactions between various biomolecules in the network.

A biological network is complex, and it is also a bridge for studying life with the thought of system science. The nodes in the network can be proteins, genes, RNA, DNA, and metabolites, etc. The edges of the network correspond to the physical, biochemical, or functional interactions between the nodes. The interaction between biomolecules is not static. It is reflected in the gene regulation network, and the edges between nodes will change due to changes in time, space or the external environment. Network analysis is the research focus of biological networks. Significant changes in the biomolecules and their interactions in the network form a differential network. This differential change has a great reference value for cell signal transduction, cell development, environmental pressure, drug treatment, and the transformation of disease states. At present, common network analysis includes gene regulatory network, protein interaction, transcription regulatory network, metabolic network, and single-cell regulatory network.

What Can Biological Network Analysis Do?

Biological network analysis is an important way to study biological organisms. Its core problem is the distance measurement of attribute dependent network and the extraction of specific attribute dependent subnet. Excavate potential changes in biological networks through biological experiment data, and study the hotspots and difficulties of life phenomena in a systematic way. For example, with the help of complex network, graph theory, information theory and other theories and methods to study protein interaction network clustering, we can understand the function of proteins. In addition, research on gene regulatory networks is increasingly applied to the fields of disease gene prediction and drug target screening, and has a profound impact on early disease diagnosis, personalized treatment, and drug research. Therefore, the construction and application of biological networks have important value and significance in theory and practice.

Regulatory Network

Regulatory network during gene expression. Fig 1. Regulatory network during gene expression.

Explore CD Genomics Biological Network Analysis Solutions


CD Genomics provides customers with different types of interaction network data analysis services. We provide biological network analysis solutions for different types of data such as proteins, RNA, DNA, single-cell, and metabolites, and present biological network analysis results in the form of interactive network diagram.

PPI Network Analysis:  To study protein interaction networks, at the protein level, mainly to study the evolutionary properties of protein interaction networks on individual proteins, and the study of protein functions, etc.

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Residue Interaction Network: The interaction network of protein residues plays an important role in understanding the structural characteristics of proteins, biological functions, and prediction of binding sites. It is of great help to disease research and drug design-related application research in the field of biomedicine.

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Gene Interaction Network: Gene regulatory network is a biological network expressing complex regulatory relationships between genes, and it is also one of the important means to understand gene functions. By constructing a gene regulatory network, we can comprehensively analyze and understand the interaction between genes, and understand and master the operating mechanism of cell life activities.

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Regulatory Network of Transcription Factors: The regulation of transcription level is an important part of gene regulation, among which transcription factor (TF) and transcription factor binding site (TFBS) are important components of transcription regulation.

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Single Cell Regulatory Network Analysis: Analyzing single-cell GRNs can help to dig deeper into the biological significance behind cell heterogeneity, and provide valuable clues for the diagnosis, treatment, and development and differentiation of diseases.

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Our Service Process

  • Transfer raw sequencing data or experimental data

  • Develop an analysis plan

  • Biological interaction network analysis

  • Generate charts

  • After-sale Services

Biomedical-Bioinformatics, a division of CD Genomics, provides a one-stop biological network analysis service according to customer's requirements. In addition to the above analysis content, we also provide circRNA and target gene interaction network analysis, metabolomics network analysis, etc. If you have any other network analysis needs, let us know and we will meet your needs. If you have any questions about the data analysis content, turnaround time and price, please feel free to contact us, we have a professional technical support team to provide the best services, and we look forward to working with you!

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

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