Feng Luo

Summary

Affiliation: Clemson University
Country: USA

Publications

  1. pmc Molecular ecological network analyses
    Ye Deng
    Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA
    BMC Bioinformatics 13:113. 2012
  2. pmc Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters
    Yuehua Zhang
    School of Computing, Clemson University, Clemson, SC 29634, USA
    Proteome Sci 10:S4. 2012
  3. pmc Snapshot of iron response in Shewanella oneidensis by gene network reconstruction
    Yunfeng Yang
    Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
    BMC Genomics 10:131. 2009
  4. pmc Characterization of the Shewanella oneidensis Fur gene: roles in iron and acid tolerance response
    Yunfeng Yang
    Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
    BMC Genomics 9:S11. 2008
  5. pmc Core and periphery structures in protein interaction networks
    Feng Luo
    School of Computing, Clemson University, Clemson, SC, USA
    BMC Bioinformatics 10:S8. 2009
  6. pmc Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions
    Bo Li
    School of Computing, Clemson University, Clemson, SC 29634, USA
    BMC Syst Biol 5:73. 2011
  7. pmc Massive-scale gene co-expression network construction and robustness testing using random matrix theory
    Scott M Gibson
    Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, South Carolina, USA
    PLoS ONE 8:e55871. 2013
  8. pmc A quantitative structure-activity relationship (QSAR) study on glycan array data to determine the specificities of glycan-binding proteins
    Pengfei Xuan
    School of Computing, Clemson University, Clemson, SC 29634, USA
    Glycobiology 22:552-60. 2012
  9. pmc Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
    Feng Luo
    Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
    BMC Bioinformatics 8:299. 2007
  10. pmc Determining thermal inactivation of Escherichia coli O157:H7 in fresh compost by simulating early phases of the composting process
    Randhir Singh
    Department of Biological Sciences, Clemson University, Clemson, South Carolina 29634, USA
    Appl Environ Microbiol 77:4126-35. 2011

Collaborators

Detail Information

Publications15

  1. pmc Molecular ecological network analyses
    Ye Deng
    Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA
    BMC Bioinformatics 13:113. 2012
    ....
  2. pmc Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters
    Yuehua 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...
  3. pmc Snapshot of iron response in Shewanella oneidensis by gene network reconstruction
    Yunfeng 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...
  4. pmc Characterization of the Shewanella oneidensis Fur gene: roles in iron and acid tolerance response
    Yunfeng 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...
  5. pmc Core and periphery structures in protein interaction networks
    Feng 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...
  6. pmc Understanding and predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using domain genetic interactions
    Bo 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...
  7. pmc Massive-scale gene co-expression network construction and robustness testing using random matrix theory
    Scott 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...
  8. pmc A quantitative structure-activity relationship (QSAR) study on glycan array data to determine the specificities of glycan-binding proteins
    Pengfei 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...
  9. pmc Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
    Feng Luo
    Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
    BMC Bioinformatics 8:299. 2007
    ....
  10. pmc Determining thermal inactivation of Escherichia coli O157:H7 in fresh compost by simulating early phases of the composting process
    Randhir Singh
    Department of Biological Sciences, Clemson University, Clemson, South Carolina 29634, USA
    Appl Environ Microbiol 77:4126-35. 2011
    ..Additionally, both the C/N ratio and the initial moisture level in the compost mix affect the rate of pathogen inactivation as well...
  11. doi request reprint Identifying differentially expressed genes in cancer patients using a non-parameter Ising model
    Xumeng 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...
  12. pmc Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules
    Jacob 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...
  13. ncbi request reprint Modular organization of protein interaction networks
    Feng 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...
  14. pmc The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks
    Stephen 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...
  15. ncbi request reprint Application of random matrix theory to microarray data for discovering functional gene modules
    Feng 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...