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The Klinke Lab @ West Virginia University

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  • Note: Search "klinke dj" 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

  1. 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
  2. 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
  3. 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.
  4. 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

Evaluates the conventional wisdom regarding the extent of beta cell destruction required before presenting with symptoms of type 1 diabetes.

  1. Klinke DJ 2nd, 'Integrating Epidemiological Data into a Mechanistic Model of Type 2 Diabetes: Validating the Prevalence of Virtual Patients", \href{http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=18046647}{(2008) \textit{Ann. Biomed. Eng.} 36:321-334.}\{5\}%[2.3]
  2. 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
  3. Klinke DJ 2nd, Validating a Dimensionless Number for Glucose Homeostasis in Humans, Ann Biomed Eng 2009; 37:1886-1896. PMID 19513847
  4. Klinke DJ 2nd, Brundage KM, Scalable analysis of flow cytometry data using R/Bioconductor, Cytometry A 2009; 75:699-706. PMID 19582872
  5. 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.
  6. Klinke DJ 2nd, An empirical Bayesian approach for model-based inference of cellular signaling networks, BMC Bioinformatics 2009; 10:371. PMID 19900289

\begin{list2} \item[] A highly accessed publication in BMC Bioinformatics. \end{list2} \item Klinke, D. J.; ``Signal Transduction Networks in Cancer: Quantitative Parameters Influence Network Topology", \href{http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=20179207}{(2010) \textit{Cancer Res} 70:1773-1782}.\{1\}%[3.8] \item Finley, S.D.; Gupta, D.; Cheng, N.; Klinke, D. J.; ``Inferring Relevant Control Mechanisms for Interleukin-12 Signaling in Na\"{i}ve CD4+ T Cells",\href{http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=20479776}{(2010) \textit{Immunol Cell Biol} \textit{in press}}.\{-\}%[3.9] \item Kulkarni, Y.; Suarez, V.; Klinke, D. J.; ``Inferring Predominant Pathways in Cellular Models of Breast Cancer Using Limited-Sample Proteomic Profiling", \href{http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=20550684}{(2010) \textit{BMC Cancer} 10:291}.\{-\}%[3.1] \item Klinke, D. J.; ``A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12", \href{http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=20843320}{(2010) \textit{Molecular Cancer} 9:242}#WVU-6 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.

  1. WVU-7 pmid 19513847

// Develops and validates a dimensionless number for the ratio of insulin production and insulin-dependent glucose metabolism in humans.

  1. WVU-8 pmid 19582872

// Provides a tutorial for using R/Bioconductor to process flow cytometry data.

  1. WVU-9 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.

  1. WVU-10 pmid 19900289

// This is a highly accessed publication in BMC Bioinformatics

  1. WVU-11 pmid 20179207

// This publication was highlighted as Research News on the Physical Sciences in Oncology website hosted by the National Cancer Institute.

  1. WVU-12 pmid 20479776

// 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.

  1. WVU-13 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.

  1. WVU-14 Klinke DJ 2nd, A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12, Molecular Cancer 2010 Sept 15; 9:242.
  2. WVU-15 Klinke DJ 2nd, Inferring the dynamic role of beta cell function in the natural history of diabetes using mathematical prototypes, 2010 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.