Live briefing
Everything about Biological network
Method of representing systems
A biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. In general, networks or graphs are used to capture relationships between entities or objects. A network can be represented as an N×N matrix where N is the number of nodes, and whose entries tell you if two nodes share an edge. Typically, this matrix will have entries of 0 or 1 with 1 denoting an edge. We can optionally use a weighted graph by assigning a weight to each edge to show how relevant the connection between two nodes is. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Biological networkA 5-minute orientation
- Skim a recent paper: Transfer learning enables predictions in network biologyInfluential work since 2022
- Pick up a classic book: Neural EngineeringThe most-reprinted book on the subject
- Read the landmark paper: Community structure in social and biological networksCited 12,563 times
- Go sideways: Biological network inferenceA closely related topic
- Go sideways: Power graph analysisA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Community structure in social and biological networks
Network biology: understanding the cell's functional organization
Biological Network Exploration with Cytoscape 3
Biological network comparison using graphlet degree distribution
Analyzing biological network parameters with CentiScaPe
Modeling cellular machinery through biological network comparison
bioDBnet: the biological database network
Dynamic Properties of Network Motifs Contribute to Biological Network Organization
🆕 Influential since 2022
Transfer learning enables predictions in network biology
Single-cell biological network inference using a heterogeneous graph transformer
BIONIC: biological network integration using convolutions
Instance segmentation of biological images using graph convolutional network
Challenges and Limitations of Biological Network Analysis
📚 Books worth reading
Neural EngineeringBin He · 2013
Bio-inspired artificial intelligenceDario Floreano · 2008- 📕Networks in cell biologyMark Buchanan, Guido Caldarelli · 2010
The Singularity Is NearRay Kurzweil · 2005
Imitation of LifeNancy Forbes · 2004
Self-organization in sensor and actor networksFalko Dressler · 2007
Self-Organizing MapsTeuvo Kohonen · 1995
Darwin among the machinesGeorge Dyson · 1997
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Biological network inference Biological network inference is the process of making inferences and predictions about biological networks. By using these networks to analyze patterns…
- Power graph analysis In computational biology, power graph analysis is a method for the analysis and representation of complex networks. Power graph analysis is the computation…
- Weighted network A weighted network is a network where the ties among nodes have weights assigned to them. A network is a system whose elements are somehow connected. The…
- Network motif Network motifs are recurrent and statistically significant subgraphs or patterns of a larger graph. All networks, including biological networks, social…
- Computational biology Computational biology is a interdisciplinary field involving the study of biological systems through the application of computer science, data analysis…
- Community structure In the study of complex networks, a network is said to have community structure if the nodes of the network can be easily grouped into (potentially overlapping)…
- Network medicine Network medicine is the application of network science towards identifying, preventing, and treating diseases. This field focuses on using network topology…
- Network theory In mathematics, computer science, and network science, network theory is a part of graph theory. It defines networks as graphs where the vertices or edges…