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The Klinke Lab @ West Virginia University

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  • Note: Search "dj+klinke" via PubGet for a third-party automatically generated set of PubMed-listed publications from the lab.

  1. Klinke DJ 2nd and Broadbelt LJ, Mechanism Reduction during Computer Generation of Compact Reaction Models, AIChE J 1997; 43:1828-1837.
  2. Klinke DJ 2nd, Wilke S, and Broadbelt LJ, A Theoretical Study of Carbon Chemisorption on Ni(111) and Co(0001) Surfaces, J Catal 1998; 178:540-554.
  3. Klinke DJ 2nd and Broadbelt LJ, Construction of a Mechanistic Model of Fischer-Tropsch Synthesis on Ni(111) and Co(0001) Surfaces, Chem Eng Sci 1999; 54:3379-3389.
    The first application of a rule-based reaction network generation algorithm to heterogeneous catalytic chemistry.
  4. Klinke DJ 2nd, Dooling DJ, and Broadbelt LJ, A Theoretical Study of Methylidyne Chemisorption on Ni(111) and Co(0001) Surfaces; Surf Sci 1999; 425:334-342.
  5. Klinke DJ 2nd and Broadbelt LJ, A Theoretical Study of Hydrogen Chemisorption on Ni(111) and Co(0001) Surfaces, Surf Sci 1999; 429:169-177.
  6. Broadbelt LJ and Klinke DJ 2nd, Kinetics of Catalyzed Reactions – D (Heterogeneous) in Encyclopedia of Catalysis, Istvan T. Horvath (Editor-in-Chief), ISBN 0-471-24183-0, pp. 4772, December 2002.
  7. Klinke DJ 2nd, The ratio of P40 monomer to dimer is an important determinant of IL-12 bioactivity, J Theor Biol 2006; 240:323-35. PMID 16448670
  8. Klinke DJ 2nd, An age-structured model of dendritic cell trafficking in the lung, Am J Physiol Lung Cell Mol Physiol 2006; 291:L1038-49. PMID 17030902
  9. Klinke DJ 2nd, A multi-scale model of dendritic cell education and trafficking in the lung: implications for T cell polarization, Ann Biomed Eng 2007; 35:937-55. PMID 17457675
  10. Klinke DJ 2nd, Integrating epidemiological data into a mechanistic model of type 2 diabetes: validating the prevalence of virtual patients, Ann Biomed Eng 2008; 36:321-34. PMID 18046647
    Provides a glimpse of the size and complexity of the proprietary PhysioLab models developed by Entelos, Inc.
  11. Klinke DJ 2nd, Extent of Beta Cell Destruction is Important but Insufficient to Predict the Onset of Type 1 Diabetes Mellitus, PLoS ONE 2008; 3:e1374. PMID 18167535
    In a review by Mark Atkinson (Curr Opin Endo Diab Obesity (2009) 16:279-285 PMID 19502978), this is highlighted as a paper of special interest with the comment: "An interesting meta-analysis that draws to the forefront, the question of, `what percentage of b cells are destroyed at the symptomatic onset of T1D?'."
  12. Klinke DJ 2nd, Ustyugova IV, Brundage K, Barnett JB, Modulating Temporal Control of NF-kappaB Activation: Implications for Therapeutic and Assay Selection, Biophys J 2008; 94:4249-4259. PMID 18281385
    Finds that our ability to observe significant biological events is limited by the signal-to-noise characteristics of the assays that we use to observe cellular responses.
  13. Klinke DJ 2nd, Validating a Dimensionless Number for Glucose Homeostasis in Humans, Ann Biomed Eng 2009; 37:1886-1896. PMID 19513847
    Develops and validates a dimensionless number for the ratio of insulin production and insulin-dependent glucose metabolism in humans.
  14. Klinke DJ 2nd, Brundage KM, Scalable analysis of flow cytometry data using R/Bioconductor, Cytometry A 2009; 75:699-706. PMID 19582872
    Provides a tutorial for using R/Bioconductor to process flow cytometry data.
  15. Leski TA, Caswell CC, Pawlowski M, Bujnicki JM, Hart SJ, Klinke DJ 2nd, Lukomski S, Identification and Classification of bcl Genes and Proteins of Bacillus cereus Group Organisms and Their Application in Bacillus anthracis Detection and Fingerprinting, Appl Environ Microbiol 2009; 75:7163-7172. PMID 19767469.
    Describes an approach to distinguish with confidence among B. anthracis strains using variability in collagen-like proteins. This addresses one of the problems with finding the perpetrators of the B. anthracis attacks on the U.S. Capital in 2001.
  16. Klinke DJ 2nd, An empirical Bayesian approach for model-based inference of cellular signaling networks, BMC Bioinformatics 2009; 10:371. PMID 19900289
    In a paper from Peter Sorger's group at Harvard (Chen et al. Genes Dev (2010) 24:1861-75. PMID 20810646), it is stated that Bayesian methods are at the forefront for using mathematical models to reason about biological systems. This highly accessed paper in BMC Bioinformatics is one of two citations provided for this statement.
  17. Klinke DJ 2nd, Signal Transduction Networks in Cancer: Quantitative Parameters Influence Network Topology, Cancer Res 2010; 70:1773-1782. PMID 20179207
    This publication was highlighted as Research News on the Physical Sciences in Oncology website hosted by the National Cancer Institute.
  18. Finley SD, Gupta D, Cheng N, Klinke DJ 2nd, Inferring Relevant Control Mechanisms for Interleukin-12 Signaling in Naive CD4+ T Cells, Immunol Cell Biol 2011; 89:100-110. PMID 20479775
    This publication uses an empirical Bayesian approach to infer the contributions of different mechanisms that regulate IL-12 signaling in naïve CD4+ T cells derived from Balb/c mice.
  19. Kulkarni Y, Suarez V, Klinke DJ 2nd, Inferring Predominant Pathways in Cellular Models of Breast Cancer Using Limited-Sample Proteomic Profiling, BMC Cancer 2010; 10:291. PMID 20550684
    This publication uses a proteomics workflow that includes 2D-gel electrophoresis and MALDI-TOF MS peptide mass fingerprinting to identify predominant pathways in two breast cancer cell models.
  20. Klinke DJ 2nd, A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12, Molecular Cancer 2010; 9:242. PMID 20843320
    This is a highly accessed paper in Molecular Cancer.
  21. Klinke DJ 2nd, Finley SD, Timescale analysis of rule-based biochemical reaction networks, Biotech Prog 2012; 28(1):33-44. PMID 21954150
    This publication describes a new approach for timescale analysis, where timescales are obtained for reaction rules (edges) rather than for reaction species (nodes).
  22. Klinke DJ 2nd, Age-corrected beta cell mass following onset of type 1 diabetes mellitus correlates with plasma C-peptide in humans, PLoS ONE 2011; 6(11):e26873. PMID 22073210
  23. Kulkarni YM, Klinke DJ 2nd, Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer, Proteome Sci 2012; 10(1):11. PMID 22357162
    This publication uses a proteomics workflow that includes 2D-gel electrophoresis and MALDI-TOF MS peptide mass fingerprinting to contrast the predominant pathways in two HER2+ breast cancer cell models against predominant pathways inferred from a normal human mammary epithelial cell line.
  24. Klinke DJ 2nd, Cheng N, Chambers E, Quantifying cross-talk among Interferon-γ, Interleukin-12 and Tumor Necrosis Factor signaling pathways within a TH1 cell model, Sci Signaling 2012; 5:ra32. PMID 22510470
    Editor's summary: The fate of T cells involved in an immune response is determined in part by the cytokine milieu. Despite our extensive knowledge of the receptors, signaling proteins, and cytokines involved, how downstream signaling pathways interact to determine T cell fate is unclear. Klinke et al. measured receptor abundance, signaling protein activation, cytokine production, and cell population changes and used these parameters to construct mathematical models to gain insights into the signaling pathways in a mouse T cell line that were stimulated by the cytokine interleukin-12 (IL-12). This combined approach uncovered previously unappreciated aspects of IL-12 signaling that determined the T cell response and serves as an example of how mathematical modeling can refine our understanding of signaling pathways.
  25. Kulkarni YM, Chambers E, McGray AJR, Ware JS, Bramson JL, Klinke DJ 2nd, A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model, Integr Biol 2012; 4(8):925-936. PMID 22777646
    Identifying local mechanisms for immunosuppression is a key knowledge gap for improving the efficacy of immunotherapies for cancer. Leveraging concepts from the analysis of physiological systems, an integrated in vitro-in silico-in vivo approach was developed to evaluate competing hypotheses regarding tumor-mediated suppression of immune response to Interleukin-12, a key cytokine that helps shape anti-tumor immunity. Collectively, the data suggest that (1) biochemical cues associated with epithelial-to-mesenchymal transition can shape anti-tumor immunity through paracrine action and (2) remnants of the immunoselective pressure associated with evolution in cancer include both sculpting of tumor antigens and expression of proteins that proactively shape anti-tumor immunity.
  26. Klinke DJ 2nd, Wang Q, Understanding Immunology via Engineering Design: The Role of Mathematical Prototyping, Comput Math Methods Med 2012; 676015. PMID 22973412.
  27. Klinke DJ 2nd, An evolutionary perspective on anti-tumor immunity, Frontiers in Oncology 2012; 2:202. PMID 23336100.
  28. Klinke DJ 2nd, In silico model-based inference: a contemporary approach for hypothesis testing in systems biology, Sci Signaling 2012; submitted.

Patents and Patent Applications

  1. Defranoux, N.A.; Dubnicoff, T.B.; Klinke, D.J.; Lewis, A.K.; Paterson, T.S.; Ramanujan, S.; Shoda, L.K.M.; Soderstrom, K.P.; Struemper, H.K.; "Method and apparatus for computer modeling a joint", US Patent #6,862,561.
  2. Kelly, S.D.; Klinke, D.J.; Leong, C.; Lewis, A.K.; Okino, M.S.; Paterson, T.S.; Shoda, L.K.M.; Stokes, C.; Struemper, H.K.; "Method and apparatus for computer modeling of an adaptive immune response", US Patent Application #10/154,123.
  3. Friedrich, C.M.; Kansal, A.; Klinke, D.J.; Michelson, S.G.; Paterson, T.S.; Polidori, D.; Trimmer, J.; Wennerberg, L.G.; "Defining Virtual Patient Populations", US Patent Application #11/346,990.
  4. Defranoux, N.A.; Dubnicoff, T.B.; Klinke, D.J.; Lewis, A.K.; Paterson, T.S.; Ramanujan, S.; Shoda, L.K.M.; Soderstrom, K.P.; Struemper, H.K.; "Method and apparatus for computer modeling a joint", US Patent #7,472,050.
  5. Klinke, D.J.; "Methods of treatment using XXXXXX antagonists", US Patent Application pending.
  6. Klinke, D.J.; "Method for screening inhibitors and identifying mechanisms of tumor-mediated immunosuppression", US Patent Application pending.