  Interactive visualization tools are highly desirable to biologist and cancer
researchers to explore the complex structures, detect patterns and find out the
relationships among bio-molecules responsible for a cancer type. A pathway
contains various bio-molecules in different layers of the cell which is
responsible for specific cancer type. Researchers are highly interested in
understanding the relationships among the proteins of different pathways and
furthermore want to know how those proteins are interacting in different
pathways for various cancer types. Biologists find it useful to merge the data
of different cancer studies in a single network and see the relationships among
the different proteins which can help them detect the common proteins in cancer
studies and hence reveal the pattern of interactions of those proteins. We
introduce the CancerLinker, a visual analytic tool that helps researchers
explore cancer study interaction network. Twenty-six cancer studies are merged
to explore pathway data and bio-molecules relationships that can provide the
answers to some significant questions which are helpful in cancer research. The
CancerLinker also helps biologists explore the critical mutated proteins in
multiple cancer studies. A bubble graph is constructed to visualize common
protein based on its frequency and biological assemblies. Parallel coordinates
highlight patterns of patient profiles (obtained from cBioportal by WebAPI
services) on different attributes for a specified cancer study
