Mehdi Pirooznia

Summary

Affiliation: Johns Hopkins University
Country: USA

Publications

  1. pmc Genomic signatures and gene networking: challenges and promises
    Ke Zhang
    Department of Pathology, Bioinformatics Core, School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND 58201, USA
    BMC Genomics 12:I1. 2011
  2. pmc SynaptomeDB: an ontology-based knowledgebase for synaptic genes
    Mehdi Pirooznia
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA
    Bioinformatics 28:897-9. 2012
  3. pmc Generation, analysis and functional annotation of expressed sequence tags from the sheepshead minnow (Cyprinodon variegatus)
    Mehdi Pirooznia
    School of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
    BMC Genomics 11:S4. 2010
  4. pmc Meta-analysis of genetic association studies on bipolar disorder
    Fayaz Seifuddin
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland 21287, USA
    Am J Med Genet B Neuropsychiatr Genet 159:508-18. 2012
  5. pmc Systematic review of genome-wide gene expression studies of bipolar disorder
    Fayaz Seifuddin
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
    BMC Psychiatry 13:213. 2013
  6. pmc Converging Evidence for Epistasis between ANK3 and Potassium Channel Gene KCNQ2 in Bipolar Disorder
    Jennifer Toolan Judy
    Department of Psychiatry, Johns Hopkins School of Medicine Baltimore, MD, USA
    Front Genet 4:87. 2013
  7. pmc SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies
    Mehdi Pirooznia
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
    Source Code Biol Med 8:8. 2013
  8. pmc A hybrid likelihood model for sequence-based disease association studies
    Yun Ching Chen
    Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, USA
    PLoS Genet 9:e1003224. 2013
  9. pmc Data mining approaches for genome-wide association of mood disorders
    Mehdi Pirooznia
    School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
    Psychiatr Genet 22:55-61. 2012

Collaborators

Detail Information

Publications9

  1. pmc Genomic signatures and gene networking: challenges and promises
    Ke Zhang
    Department of Pathology, Bioinformatics Core, School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND 58201, USA
    BMC Genomics 12:I1. 2011
    ..We hope this supplement presents the current computational and statistical challenges faced in genomics studies, and shows the enormous promises and opportunities in the genomic future...
  2. pmc SynaptomeDB: an ontology-based knowledgebase for synaptic genes
    Mehdi Pirooznia
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, MD, USA
    Bioinformatics 28:897-9. 2012
    ..However, while the tools and databases available for the annotation of high-throughput DNA and protein are generally robust, a comprehensive resource dedicated to the integration of information about the synapse is lacking...
  3. pmc Generation, analysis and functional annotation of expressed sequence tags from the sheepshead minnow (Cyprinodon variegatus)
    Mehdi Pirooznia
    School of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
    BMC Genomics 11:S4. 2010
    ..Here, we initiated a project to sequence and analyze over 10,000 ESTs generated from the Sheepshead minnow (Cyprinodon variegatus) as a resource for investigating stressor responses...
  4. pmc Meta-analysis of genetic association studies on bipolar disorder
    Fayaz Seifuddin
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland 21287, USA
    Am J Med Genet B Neuropsychiatr Genet 159:508-18. 2012
    ..The results of this meta-analysis and from other on-going genomic experiments in BP are available online at Metamoodics (http://metamoodics.igm.jhmi.edu)...
  5. pmc Systematic review of genome-wide gene expression studies of bipolar disorder
    Fayaz Seifuddin
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
    BMC Psychiatry 13:213. 2013
    ..These studies are heterogeneous, underpowered and use overlapping samples. We conducted a systematic review of these studies to synthesize the current findings...
  6. pmc Converging Evidence for Epistasis between ANK3 and Potassium Channel Gene KCNQ2 in Bipolar Disorder
    Jennifer Toolan Judy
    Department of Psychiatry, Johns Hopkins School of Medicine Baltimore, MD, USA
    Front Genet 4:87. 2013
    ..The interactions between ANK3 and KCNQ2 merit further investigation, and if confirmed, may motivate a new line of research into a novel therapeutic target for BP...
  7. pmc SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies
    Mehdi Pirooznia
    Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
    Source Code Biol Med 8:8. 2013
    ..Using SVA increases the biological accuracy and reproducibility of gene expression studies by identifying these sources of heterogeneity and correctly accounting for them in the analysis...
  8. pmc A hybrid likelihood model for sequence-based disease association studies
    Yun Ching Chen
    Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, USA
    PLoS Genet 9:e1003224. 2013
    ..05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing...
  9. pmc Data mining approaches for genome-wide association of mood disorders
    Mehdi Pirooznia
    School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
    Psychiatr Genet 22:55-61. 2012
    ..Data mining methods are available that may be applied to analyze the high dimensional data generated by GWAS of complex psychiatric disorders...