Multiple partitions alignment via spectral rotation

Multiple network alignment via multiMAGNA+.

Network alignment (NA) aims to find a node mapping that identifies topologically or functionally similar network regions between molecular networks of different species. Analogous to genomic sequence alignment, NA can be used to transfer biological knowledge from well- to poorly-studied species between aligned network regions. Pairwise NA (PNA) finds similar regions between two networks while m...

Multiple description coding via scaling-rotation transform

Nonlinear magneto-optical rotation via alignment-to-orientation conversion

Nonlinear magneto-optical rotation is investigated at high light powers where the rotation is significantly modified by ac Stark shifts. These shifts are shown to change the overall sign of rotation for closed F-->F+1 transitions compared to the low light power limit. The effect is demonstrated by measurements in rubidium and density matrix calculations. The results are important for applicatio...

Image alignment via kernelized feature learning

Machine learning is an application of artificial intelligence that is able to automatically learn and improve from experience without being explicitly programmed. The primary assumption for most of the machine learning algorithms is that the training set (source domain) and the test set (target domain) follow from the same probability distribution. However, in most of the real-world application...

Local Multiple Alignment Via Subgraph Enumeration

We discuss three problems, which we call blocking, chaining and jattenitrg, that arise when computing a multiple-sequence alignment from given pairwise alignments. Blocking is the construction of gap-free multiple alignments, each called a “block”, from the pairwise alignments; it is formalized here as the enumeration of maximal cliques in a certain graph. Chaining is the identification of a co...