The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
— Biological networks are formalized summaries of our knowledge about interactions among biological system components, like genes, proteins, or metabolites. From their global top...
Networks continue to change to support new applications, improve reliability and performance and reduce the operational cost. The changes are made to the network in the form of up...
Ajay Anil Mahimkar, Han Hee Song, Zihui Ge, Aman S...