Suggestive linkage to a neighboring region of IRF6 in a cleft lip and palate multiplex family

Cleft lip and/or palate (CL/P) is a common congenital malformation with a complex etiology, as many genes and environmental factors have been shown to play a role in craniofacial development. We used a genetic mapping approach to analyze a family with multiplex CL/P. A genome-wide scan with a 10 kb single nucleotide polymorphism (SNP) chip followed by fine mapping with microsatellite markers in a CL/P multiplex family suggested linkage (maximum multipoint LOD score of 2.41) to a 6.5 Mb interval at 1q32.1-q32.2. This interval was close to, but excluded IRF6. Mutations in the IRF6 (1q32.2) cause syndromic forms of CL/P, and several association studies have shown that polymorphisms in and around IRF6 are associated with non-syndromic CL/P (NSCLP). However, in the family described here, IRF6 was excluded from the linkage interval. Sequencing of selected genes in the interval and comparative genome hybridization (CGH) did not reveal any mutations or genomic aberrations. Our data suggest that an unidentified CL/P gene, or a non-coding IRF6 regulatory element in this linkage interval may have caused CL/P in this family

Solving Graph Isomorphism using Parameterized Matching

Abstract. We propose a new approach to solve graph isomorphism using parameterized matching. To find isomorphism between two graphs, one graph is linearized, i.e., represented as a graph walk that covers all nodes and edges such that each element is represented by a parameter. Next, we match the graph linearization on the second graph, searching for a bijective function that maps each element of the first graph to an element of the second graph. We develop an efficient linearization algorithm that generates short linearization with an approximation guarantee, and develop a graph matching algorithm. We evaluate our approach experimentally on graphs of different types and sizes, and compare to the performance of VF2, which is a prominent algorithm for graph isomorphism. Our empirical measurements show that graph linearization finds a matching graph faster than VF2 in many cases because of better pruning of the search space. 1 Introduction and Related Wor

Nearly Exact Mining of Frequent Trees in Large Networks

Mining frequent patterns in a single network (graph) poses a number of challenges. Already only to match one path pattern to a network (upto subgraph isomorphism) is NP-complete. Matching algorithms that exist, become intractable even for reasonably small patterns, on networks which are large or have a high average degree. Based on recent advances in parameterized complexity theory, we propose a novel miner for rooted trees in networks. The miner, for a fixed parameter k (maximal pattern size), can mine all rooted trees with delay linear in the size of the network and only mildly exponential in the fixed parameter k (2 k ). This allows us to mine tractably, rooted trees, in large networks such as the WWW or social networks. We establish the practical applicability of our miner, by presenting an experimental evaluation on both synthetic and real-world data. © 2012 Springer-Verlag.status: publishe