Computing shortest paths between two given nodes is a fundamental operation over graphs, but known to be nontrivial over large disk-resident instances of graph data. While a numbe...
Andrey Gubichev, Srikanta J. Bedathur, Stephan Seu...
The avMlability of large EST(Expressed Sequence Tag)databases has led to a revolution in the waynew genes are cloned. Difficulties arise, however,due to high error rates and redun...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
This book covers the following topics: The biological paradigm, Threshold logic, Weighted Networks, The Perceptron, Perceptron learning, Unsupervised learning and clustering algori...
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...