Network Analysis Service in Biology

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