A multi-dimensional, time-lapse, high content screening platform applied to schistosomiasis drug discovery.

Approximately 10% of the world's population is at risk of schistosomiasis, a disease of poverty caused by the Schistosoma parasite. To facilitate drug discovery for this complex flatworm, we developed an automated high-content screen to quantify the multidimensional responses of Schistosoma mansoni post-infective larvae (somules) to chemical insult. We describe an integrated platform to process worms at scale, collect time-lapsed, bright-field images, segment highly variable and touching worms, and then store, visualize, and query dynamic phenotypes.

The SMAL web server: global multiple network alignment from pairwise alignments.

Motivation: Alignments of protein-protein interaction networks (PPIN) can be used to predict protein function, study conserved aspects of the interactome, and to establish evolutionary correspondences. Within this problem context, determining multiple network alignments (MNA) is a significant challenge that involves high computational complexity. A limited number of public MNA implementations are available currently and the majority of the pairwise network alignment (PNA) algorithms do not have MNA counterparts.

Global multiple protein-protein interaction network alignment by combining pairwise network alignments.

Background: A wealth of protein interaction data has become available in recent years, creating an urgent need for powerful analysis techniques. In this context, the problem of finding biologically meaningful correspondences between different protein-protein interaction networks (PPIN) is of particular interest. The PPIN of a species can be compared with that of other species through the process of PPIN alignment.