Vivek Jayaswal

Summary

Affiliation: University of Sydney
Country: Australia

Publications

  1. pmc Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, Australia
    Nucleic Acids Res 37:e60. 2009
  2. pmc Identification of microRNA-mRNA modules using microarray data
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia
    BMC Genomics 12:138. 2011
  3. pmc VAN: an R package for identifying biologically perturbed networks via differential variability analysis
    Vivek Jayaswal
    School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
    BMC Res Notes 6:430. 2013
  4. doi request reprint Molecular interaction networks for the analysis of human disease: utility, limitations, and considerations
    Sarah Jane Schramm
    Sydney Medical School, Westmead Millennium Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia Melanoma Institute Australia, Sydney, NSW, Australia
    Proteomics 13:3393-405. 2013
  5. pmc miR-10a is aberrantly overexpressed in Nucleophosmin1 mutated acute myeloid leukaemia and its suppression induces cell death
    Adam Bryant
    Blood, Stem Cells and Cancer Research, St Vincent s Centre for Applied Medical Research, St Vincent s Hospital, Sydney, NSW, Australia
    Mol Cancer 11:8. 2012
  6. pmc Measures of association for identifying microRNA-mRNA pairs of biological interest
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia
    PLoS ONE 7:e29612. 2012
  7. doi request reprint Expression profiling of cytogenetically normal acute myeloid leukemia identifies microRNAs that target genes involved in monocytic differentiation
    Mark Lutherborrow
    Blood, Stem Cells and Cancer Research, St Vincent Centre for Applied Medical Research, St Vincent s Hospital and St Vincent s Clinical School, University of New South Wales, Darlinghurst, NSW, Australia
    Am J Hematol 86:2-11. 2011
  8. pmc MicroRNA-155 as an inducer of apoptosis and cell differentiation in Acute Myeloid Leukaemia
    Catalina A Palma
    Blood, Stem Cells and Cancer Research, St Vincent s Centre for Applied Medical Research, St Vincent s Hospital, Sydney, Australia
    Mol Cancer 13:79. 2014
  9. doi request reprint Disturbed protein-protein interaction networks in metastatic melanoma are associated with worse prognosis and increased functional mutation burden
    Sarah Jane Schramm
    Sydney Medical School, The University of Sydney at Westmead Millennium Institute for Medical Research, Sydney, NSW, Australia
    Pigment Cell Melanoma Res 26:708-22. 2013
  10. doi request reprint Mixture models of nucleotide sequence evolution that account for heterogeneity in the substitution process across sites and across lineages
    Vivek Jayaswal
    School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia CSIRO Ecosystem Sciences, Canberra, ACT 2601, Australia and Centre for Mathematical Biology, University of Sydney, Sydney, NSW 2006, AustraliaSchool of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia CSIRO Ecosystem Sciences, Canberra, ACT 2601, Australia and Centre for Mathematical Biology, University of Sydney, Sydney, NSW 2006, Australia
    Syst Biol 63:726-42. 2014

Collaborators

Detail Information

Publications13

  1. pmc Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, Australia
    Nucleic Acids Res 37:e60. 2009
    ..A literature survey revealed that some of the miRNAs that were predicted to be regulatory, were indeed oncogenic or tumor suppressors. Finally, some of the predicted miRNA targets have been shown to be experimentally valid...
  2. pmc Identification of microRNA-mRNA modules using microarray data
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia
    BMC Genomics 12:138. 2011
    ..However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs...
  3. pmc VAN: an R package for identifying biologically perturbed networks via differential variability analysis
    Vivek Jayaswal
    School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
    BMC Res Notes 6:430. 2013
    ..Here, we present the Variability Analysis in Networks (VAN) software package: a collection of R functions to streamline this bioinformatics analysis...
  4. doi request reprint Molecular interaction networks for the analysis of human disease: utility, limitations, and considerations
    Sarah Jane Schramm
    Sydney Medical School, Westmead Millennium Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia Melanoma Institute Australia, Sydney, NSW, Australia
    Proteomics 13:3393-405. 2013
    ..We present options for researchers intending to use large-scale molecular interaction networks as a functional context for protein or gene expression data, including microRNAs, especially in the context of human disease. ..
  5. pmc miR-10a is aberrantly overexpressed in Nucleophosmin1 mutated acute myeloid leukaemia and its suppression induces cell death
    Adam Bryant
    Blood, Stem Cells and Cancer Research, St Vincent s Centre for Applied Medical Research, St Vincent s Hospital, Sydney, NSW, Australia
    Mol Cancer 11:8. 2012
    ..We utilised microRNA microarrays and functional assays to determine if microRNA dysregulation could be involved in the pathogenesis of in NPM1 mutated (NPM1mut)-AML...
  6. pmc Measures of association for identifying microRNA-mRNA pairs of biological interest
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia
    PLoS ONE 7:e29612. 2012
    ..We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation...
  7. doi request reprint Expression profiling of cytogenetically normal acute myeloid leukemia identifies microRNAs that target genes involved in monocytic differentiation
    Mark Lutherborrow
    Blood, Stem Cells and Cancer Research, St Vincent Centre for Applied Medical Research, St Vincent s Hospital and St Vincent s Clinical School, University of New South Wales, Darlinghurst, NSW, Australia
    Am J Hematol 86:2-11. 2011
    ....
  8. pmc MicroRNA-155 as an inducer of apoptosis and cell differentiation in Acute Myeloid Leukaemia
    Catalina A Palma
    Blood, Stem Cells and Cancer Research, St Vincent s Centre for Applied Medical Research, St Vincent s Hospital, Sydney, Australia
    Mol Cancer 13:79. 2014
    ..This study investigated the effects of modulating miR-155 expression in human AML cells, and its mechanism of action...
  9. doi request reprint Disturbed protein-protein interaction networks in metastatic melanoma are associated with worse prognosis and increased functional mutation burden
    Sarah Jane Schramm
    Sydney Medical School, The University of Sydney at Westmead Millennium Institute for Medical Research, Sydney, NSW, Australia
    Pigment Cell Melanoma Res 26:708-22. 2013
    ..The disturbed regions of networks are therefore markers of clinically relevant, selectable tumor evolution in melanoma which may carry driver mutations. ..
  10. doi request reprint Mixture models of nucleotide sequence evolution that account for heterogeneity in the substitution process across sites and across lineages
    Vivek Jayaswal
    School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia CSIRO Ecosystem Sciences, Canberra, ACT 2601, Australia and Centre for Mathematical Biology, University of Sydney, Sydney, NSW 2006, AustraliaSchool of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia CSIRO Ecosystem Sciences, Canberra, ACT 2601, Australia and Centre for Mathematical Biology, University of Sydney, Sydney, NSW 2006, Australia
    Syst Biol 63:726-42. 2014
    ..cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus, implying that they might have become so selectively constrained that they could be considered invariable sites in these species...
  11. doi request reprint MicroRNA and mRNA expression profiling in metastatic melanoma reveal associations with BRAF mutation and patient prognosis
    Varsha Tembe
    Westmead Millennium Institute, The University of Sydney, Sydney, NSW, Australia Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
    Pigment Cell Melanoma Res 28:254-66. 2015
    ..miRNAs overexpressed in association with PP in an autoregulatory fashion will not be suitable therapeutic targets. ..
  12. pmc Gene profiling reveals association between altered Wnt signaling and loss of T-cell potential with age in human hematopoietic stem cells
    Melissa L M Khoo
    Blood Stem Cells and Cancer Research, St Vincent s Centre for Applied Medical Research, and The University of New South Wales, Sydney, NSW, 2010, Australia
    Aging Cell 13:744-54. 2014
    ....
  13. doi request reprint Reducing model complexity of the general Markov model of evolution
    Vivek Jayaswal
    School of Mathematics and Statistics, University of Sydney, NSW, Australia
    Mol Biol Evol 28:3045-59. 2011
    ..This problem can be alleviated by including more complex models during the model selection. We present a novel heuristic that evaluates a small fraction of these complex models and identifies the optimal model...