SUMMARY: Many online sources of gene interaction networks supply rich visual data regarding gene pathways that can aid in the study of biological processes, disease research and drug discovery. PathGen incorporates data from several sources to create transitive connections that span multiple gene interaction databases. Results are displayed in a comprehensible graphical format, showing gene interaction type and strength, database source and microarray expression data. These features make PathGen a valuable tool for in silico discovery of novel gene interaction pathways, which can be experimentally tested and verified. The usefulness of PathGen interaction analyses was validated using genes connected to the altered facial development related to Down syndrome. AVAILABILITY: http://dna.cs.byu.edu/pathgen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Further information is available at http://dna.cs.byu.edu/pathgen/PathGenSupplemental.pdf.

Plagiarism is a serious problem that infringes copyrighted documents/materials, which is an unethical practice and decreases the economic incentive received by authors (owners) of the original copies. Unfortunately, plagiarism is getting worse due to the increasing number of on-line publications on the Web, which facilitates locating and paraphrasing information. In solving this problem, we propose a novel plagiarism-detection method, called SimPaD, which (i) establishes the degree of resemblance between any two documents D1and D2based on their sentence-to-sentence similarity computed by using pre-defined word-correlation factors, and (ii) generates agraphical view of sentences that are similar (or the same) in D1and D2. Experimental results verify that SimPaD is highly accurate in detecting (non-) plagiarized documents and outperforms existing plagiarism-detection approaches.