Biological systems are often represented as networks of complex sets of binary interactions or relations between different entities. Essentially, every biological entity has interactions with other biological entities, from the molecular to the ecosystem level, providing us with the opportunity to model biology using many different types of networks such as ecological, neurological, metabolic or molecular interaction networks. Systems biology aims to understand biological entities at the systemic level, analyzing them not only as individual components, but also as interacting systems and their emergent properties. Related to this is network biology which allows the representation and analysis of biological systems using tools derived from graph theory.

Overall Solution

• Different types of information can be represented in the shape of networks in order to model the cell. The meaning of the nodes and edges used in a network representation depends on the type of data used to build the network.
• Different types of data will also produce different general network characteristics in terms of connectivity, complexity and structure, where edges and nodes potentially convey multiple layers of information.

Our Network analysis services in biology

Different types of biological networks we can provide include:

1. Protein-protein interaction networks

• Represent the physical relationships between proteins. They are central to practically every process that takes place in the cell.
• Proteins are represented as nodes that are linked by undirected edges.

2. Metabolic networks

• Represent the biochemical reactions that allow an organism to grow, reproduce, respond to the environment and maintain its structure.
• Metabolites and enzymes take the role of nodes and the reactions describing their transformations are represented as directed edges.
• Edges can represent the direction of the metabolic flow or regulatory effects of a specific reaction.

3. Gene/transcriptional regulatory networks

Genes and transcription factors are represented as nodes, while the relationship between them is depicted by different types of directional edges.

4. Cell signalling networks

• Signalling pathways represent the ordered sequences of events and model the information flow within the cell.
• Gene regulation networks can be considered as a sub-type of cell signalling networks, focusing on a specific signalling event which is often the final stage of a signalling cascade.

5. Genetic interaction networks

• Genetic interaction is the synergistic phenomenon where the phenotype resulting from simultaneous mutations in two or more genes is significantly different from the phenotype that would result from adding the effects of the individual mutations.
• Represent a functional relationship between different genes, rather than a physical one.
• Genes are represented as nodes and their relationships as edges. Depending on the type of evidence behind the interaction, directionality can be inferred for the edges.

Our Advantages

• CD ComputaBio can provide you with many different biological network analysis services.
• Our biological network analysis services have high accuracy.
• The analysis structure we provide helps your research and topics.

CD ComputaBio provides corresponding network analysis services in biology. Our network analysis services in biology have proven to be very useful for understanding the biochemical basis of physiological events at different stages of drug development (even in different fields such as materials science). CD ComputaBio team has been working in this field for more than ten years and has published his findings in top scientific journals. If you have a need for network analysis services, please feel free to contact us.

We provide a variety of modeling services, but not limited to:

• Residue Interaction Network Service
• PPI Network Service

Network Analysis Service in Biology

• • Q: What are the basic characteristics of the network?

    • A:

      Degree: A degree of a node is a number of edges in a network that connect node with its neighbors.

      Connectivity: A connectivity represents minimum number edges that need to be removed to make a disconnected graph.

      Shortest path: A shortest path is a path in which the two nodes are connected by the smallest number of intermediate nodes.

      Closeness: A closeness centrality of a node is the reciprocal of the average shortest path length.

      Betweenness centrality: A betweenness centrality of a node is the number of times that a node is included in the shortest path between each pair of nodes, normalized by the total number of pairs.

  • Q: What can network analysis service help us do?

    • A:

      Network analysis may help in choosing the right pose in protein-protein docking, which is important for selecting inhibitor binding sites.

      Network analysis facilitates the search for variable conformation sites and the study of the mechanism of intra-protein signaling.

      The development of protein-protein interaction inhibitors is a promising approach to drug design, and networks demonstrate their suitability for this purpose.

  • Q: How to place an order for network analysis?

    • A: You just need to provide us with the raw files of molecular dynamics simulations, and we can perform network analysis services. If you do not have the relevant trajectory files, we also provide a one-stop analysis service including molecular dynamics simulations. If the calculation demand is clear, you can directly choose the corresponding project on the CD ComputaBio website to make an appointment, and you need to fill in the specific calculation materials and calculation requirements when making an appointment. If you are not sure of the calculation content, you can contact the staff directly for demand communication.

  • Q: Do you offer advanced data mining services?

    • A: Through our network analysis services, we can also provide the following data mining services:

      Prediction of protein-interaction sites.

      Reliability assessment of protein-protein interactions.

      Establishment of interaction networks for specific protein collections and involvement in pathological/physiological processes.
  • Q: What specific network analysis services can you provide?

    • A: We offer you the folloing network analysis services for you to choose from:

      Residue lnteraction Network Service

      PPI Network Service

      Gene Co-Expression Network Analysis

      MicroRNA and Target Gene Network DiagramService

      Transcription Factor Analysis and NetworkConstruction Service

      Co-expression Network Analysis service oflncRNA and mRNA

      ceRNA Regulatory Network ConstructionService

      Time Series Co-expression NetworkConstruction Service

      GSEA Analysis

      Pathway and Network AnalysisWGCNA Network Service

      Series Test of Cluster Service

      Gene Interaction Network Analysis Service
  • Q: What are the application areas of network analysis?

    • A: With our network analysis service, you can apply the results to the following areas:

      Cancer

      Mouse Genetics

      Yeast genetics

      Brain imaging data analysis
  • Q: Why should I choose CD ComputaBio?

    • A: CD ComputaBio is one of the leading computational biology companies in the world, is now open to provide web analysis services to our clients. With years of experience in the field of bioinformatics, we are ready to provide our clients with the most outstanding service!