Research Topics
Genomes and GenesSpecies | Feng LuoSummaryAffiliation: Clemson University Country: USA Publications
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Detail Information
Publications
Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theoryFeng Luo
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
BMC Bioinformatics 8:299. 2007....
Modular organization of protein interaction networksFeng Luo
Department of Computer Science, 100 McAdams Hall, Clemson University, Clemson, SC 29634 0974, USA
Bioinformatics 23:207-14. 2007..Accumulating evidence suggests that biological systems are composed of interacting, separable, functional modules. Identifying these modules is essential to understand the organization of biological systems...- Snapshot of iron response in Shewanella oneidensis by gene network reconstructionYunfeng Yang
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
BMC Genomics 10:131. 2009..In this work, we integrate physiological, transcriptomics and genetic approaches to delineate the iron response of S. oneidensis... - Application of random matrix theory to microarray data for discovering functional gene modulesFeng Luo
Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, South Carolina 29634, USA
Phys Rev E Stat Nonlin Soft Matter Phys 73:031924. 2006..This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules... - Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactionsBo Li
School of Computing, Clemson University, Clemson, SC 29634, USA
BMC Syst Biol 5:73. 2011..Synthetic lethal genetic interactions among proteins have been widely used to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions is still unclear... 
Identifying differentially expressed genes in cancer patients using a non-parameter Ising modelXumeng Li
School of Computing, Clemson University, Clemson, SC, USA
Proteomics 11:3845-52. 2011..Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model...- A dynamically growing self-organizing tree (DGSOT) for hierarchical clustering gene expression profilesFeng Luo
Department of Computer Science, University of Texas at Dallas, Richardson, TX 75252, USA
Bioinformatics 20:2605-17. 2004..Furthermore, the biological functionality enrichment in the clusters is considerably high and the hierarchical structure of the clusters is more reasonable. AVAILABILITY: DGSOT is available upon request from the authors... - Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modulesJacob B Spangler
Department of Genetics and Biochemistry, Clemson University, Clemson, South Carolina, United States of America
PLoS ONE 7:e45041. 2012..Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome... - A quantitative structure-activity relationship (QSAR) study on glycan array data to determine the specificities of glycan-binding proteinsPengfei Xuan
School of Computing, Clemson University, Clemson, SC 29634, USA
Glycobiology 22:552-60. 2012..Our approach will facilitate the glycan-binding specificity analysis using the glycan array. A user-friendly web tool of the QSAR method is available at http://bci.clemson.edu/tools/glycan_array... - Characterization of the Shewanella oneidensis Fur gene: roles in iron and acid tolerance responseYunfeng Yang
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
BMC Genomics 9:S11. 2008..In many bacterial species, coordinate regulation of iron homeostasis depends on the protein product of a Fur gene. Fur also plays roles in virulence, acid tolerance, redox-stress responses, flagella chemotaxis and metabolic pathways... - The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networksStephen P Ficklin
Plant and Environmental Sciences, Clemson University, Clemson, South Carolina 29634, USA
Plant Physiol 154:13-24. 2010..Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes... - Core and periphery structures in protein interaction networksFeng Luo
School of Computing, Clemson University, Clemson, SC, USA
BMC Bioinformatics 10:S8. 2009..Characterizing the structural properties of protein interaction networks will help illuminate the organizational and functional relationships among elements in biological systems... - Massive-scale gene co-expression network construction and robustness testing using random matrix theoryScott M Gibson
Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, South Carolina, USA
PLoS ONE 8:e55871. 2013..Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust... - Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clustersYuehua Zhang
School of Computing, Clemson University, Clemson, SC 29634, USA
Proteome Sci 10:S4. 2012..Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear... - Discrete surface Ricci flowMiao Jin
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794 4400, USA
IEEE Trans Vis Comput Graph 14:1030-43. 2008..They have the potential for a wide range of applications in graphics, geometric modeling, and medical imaging. We demonstrate their practical values by global surface parameterizations... - Identification and characterization of CPS1 as a hyaluronic acid synthase contributing to the pathogenesis of Cryptococcus neoformans infectionAmbrose Jong
Division of Hematology Oncology, Children s Hospital Los Angeles, Los Angeles, CA 90027, USA
Eukaryot Cell 6:1486-96. 2007..Together, our results support that C. neoformans CPS1 encodes hyaluronic acid synthase and that its product, hyaluronic acid, plays a role as an adhesion molecule during the association of endothelial cells with yeast... - Hemodynamic and metabolic changes induced by cocaine in anesthetized rat observed with multimodal functional MRIKarl F Schmidt
Center for Comparative NeuroImaging, University of Massachusetts, Worcester, MA, USA
Psychopharmacology (Berl) 185:479-86. 2006.... - Adaptive evolution after gene duplication in alpha-KT x 14 subfamily from Buthus martensii KarschZhijian Cao
State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, PR China
IUBMB Life 57:513-21. 2005.... - Optimal surface parameterization using inverse curvature mapYong Liang Yang
Department of Computer Science and Technology, Tsinghua University, Beijing, China
IEEE Trans Vis Comput Graph 14:1054-66. 2008..Comparisons are conducted with existing methods and using different energies. Novel parameterization applications are also introduced...