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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Biological network | 3/5 | https://en.wikipedia.org/wiki/Biological_network | reference | science, encyclopedia | 2026-05-05T14:01:40.853976+00:00 | kb-cron |
Network medicine is an emerging field that applies network principles to understand the molecular basis of human disease. Instead of focusing on single genes or proteins, network medicine examines how diseases arise from small changes in complex biological networks, including protein-protein interaction networks, gene regulatory networks, and metabolic pathways. Within this framework, diseases are associated with specific “disease modules,” defined as groups of interconnected components whose collective dysfunction contributes to a pathological state. This network based perspective enables the identification of disease associated genes, the analysis of relationships between different diseases, and the development of therapeutic strategies that target multiple components of a biological system rather than a single molecule. Network medicine also supports approaches such as drug repurposing and the integration of large-scale omics data, providing a systems-level complement to traditional reductionist methods and contributing to advances in precision medicine.
=== Between-species interaction networks === In biology, pairwise interactions have historically been the focus of intense study. With the recent advances in network science, it has become possible to scale up pairwise interactions to include individuals of many species involved in many sets of interactions to understand the structure and function of larger ecological networks. The use of network analysis can allow for both the discovery and understanding of how these complex interactions link together within the system's network, a property that has previously been overlooked. This powerful tool allows for the study of various types of interactions (from competitive to cooperative) using the same general framework. For example, plant-pollinator interactions are mutually beneficial and often involve many different species of pollinators as well as many different species of plants. These interactions are critical to plant reproduction and thus the accumulation of resources at the base of the food chain for primary consumers, yet these interaction networks are threatened by anthropogenic change. The use of network analysis can illuminate how pollination networks work and may, in turn, inform conservation efforts. Within pollination networks, nestedness (i.e., specialists interact with a subset of species that generalists interact with), redundancy (i.e., most plants are pollinated by many pollinators), and modularity play a large role in network stability. These network properties may actually work to slow the spread of disturbance effects through the system and potentially buffer the pollination network from anthropogenic changes somewhat. More generally, the structure of species interactions within an ecological network can tell us something about the diversity, richness, and robustness of the network. Researchers can even compare current constructions of species interactions networks with historical reconstructions of ancient networks to determine how networks have changed over time. Much research into these complex species interactions networks is highly concerned with understanding what factors (e.g., species richness, connectance, nature of the physical environment) lead to network stability.