Suzanne Renick Gallagher

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Modeling protein interaction data with graphs (networks) is insufficient for some common types of experimentally generated interaction data. For example, in affinity purification experiments, one protein is pulled out of the cell along with other proteins that are bound to it. This data is not intrinsically binary, so we lose information when we model it(More)
Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of(More)
Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the(More)
Disease-gene networks are bipartite networks that connect diseases to the genes with which they are associated. Due to the absence of tools to analyze bipartite networks, however, they are usually analyzed by "projecting" the bipartite network into a unipartite one by taking one side of the bipartition as the nodes and connecting two nodes if they share a(More)
The <i>edge (vertex) connectivity</i> of a graph is the minimum number of edges (vertices) that must be removed to disconnect the graph. Connectivity is an important property of a graph but has seldom been used in the study of protein-protein interaction (PPI) and other biological networks. Connectivity differs from edge density in that it is based on the(More)
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