Complex Network Analysis Service

Complex networks generally exist in the real world. The network cluster structure with small-world and scale-free statistical characteristics is one of the important topological properties of complex networks. The use of clustering algorithms in complex biological networks to reveal the cluster structure of biological networks is of great significance for analyzing the topology of biological networks and predicting their functions. The study of complex network clustering methods has important theoretical significance and broad application prospects for analyzing the topological structure of complex networks, understanding the functions of complex networks, and predicting the behavior of complex networks. The current applications in complex biological networks are mainly concentrated in the areas of protein interaction network analysis and prediction of unknown protein functions, metabolic network analysis, protein similarity network analysis and gene regulation network analysis.

Features of complex network

In short, a complex network is a highly complex network. The main manifestations of its complexity are as follows:

• The complex structure is mainly manifested by the huge number of nodes and the network structure presents many different characteristics.
• Connection diversity: The connection weights between nodes are different, and there may be directionality.
• Dynamic complexity: The node set may belong to a nonlinear dynamic system, for example, the node state changes complexly over time.
• Node diversity: nodes in a complex network can represent anything.

Overall solutions

CD ComputaBio has many years of experience in the research of biological complex networks. In the past years, we have worked with many research institutes and pharmaceutical companies to solve problems related to complex networks for customers. We can provide you with the following services but not limited to:

• Protein-protein interaction networks
  The protein interaction network is composed of individual proteins through their interactions with each other to participate in all aspects of life processes such as biological signal transmission, gene expression regulation, energy and material metabolism, and cell cycle regulation.
• Protein-ligand interaction networks
  The protein-small molecule interaction network is composed of proteins that interact with each other to participate in all aspects of life processes such as biological signal transmission, gene expression regulation, energy and material metabolism.
• Metabolic networks
  Metabolic networks represents the biochemical reactions that allow an organism to grow, reproduce, respond to the environment and maintain its structure.
• Gene/transcriptional regulatory networks
• Cell signalling networks
• Genetic interaction networks