Chengpeng (Charlie) Bi
Ph.D. 2002 The Pennsylvania State University

Director of Bioinformatics & Intelligent Computing
Division of Clinical Pharmacology and Therapeutic Innovation
Children's Mercy Hospital, Kansas City, MO 64108 USA

Joint faculty appointments with UMKC (non-tenure track):
Assistant Professor of Pediatrics, UMKC School of Medicine
Kansas City, Missouri 64108 USA
         C Bi

Contact: cbi at cmh dot edu

Link: curriculum vitae (short 2010 | biosketch 2015)

Servers: BiPad | Bilogo plotter | GEMFA | WebSIDD | PMC | SpliceSite Scanner |

Teaching: Advanced Algorithms in Bioinformatics (graduate course)

Publications in: PubMed | Google Scholar |

    [2017]

  1. Construction of LMS values for MUAC z-score determination in U.S. children 2 months through 18 years of age. Nutrition in Clinical Practice 2017 Feb 19;32(1):68-76.
    ** Co-authored with Susan M. Abdel-Rahman, Charlie Bi, Kristi Thaete
  2. Metabolic and molecular insights into an essential role of nicotinamide phosphoribosyltransferase. Cell Death & Disease 8(3):e2705, March 2017.
    ** Co-authored with Li Q Zhang, Leon Van Haandel, Min Xiong, Peixin Huang, Daniel P Heruth, Charlie Bi, Roger Gaedigk, Xun Jiang, Ding-You Li,Gerald Wyckoff, Dmitry N Grigoryev, Li Gao, Linheng Li, Min Wu, J Steven Leeder and Shui Qing Ye
  3. Age-related changes in the pediatric liver transcriptome. the 10th Annual Innovations in Design, Analysis and Dissemination: Frontiers in Biostatistical Methods conference, April 27 - 28, 2017, University of Kansas - Edwards Campus, Overland Park, Kansas.
    ** Co-authored with Richard Meier, Charlie Bi, Roger Gaedigk, Shui Qing Ye, Dan Heruth, J. Steven Leeder, Brooke L. Fridley

    [2016]

  4. Transcriptional Regulators Predict CYP3A4 Expression in Human Pediatric Liver. Annual Meeting of the American Society of Pharmacology and Experimental Therapeutics (ASPET 2016), San Diego, CA USA April 2 to April 6, 2016 (Poster Abstract)
    ** Co-authored with Carrie A. Vyhlidal, Chengpeng Bi, Shui Q. Ye, J. Steven Leeder
  5. Building a Clinician-Driven, EHR-Embedded, Busulfan-Pharmacokinetic Decision Support Tool (DST) for the Point-of-Care Clinician. 2016 Pediatric Academic Society (PAS) Annual Meeting, April 30-May 3, 2016 Baltimore, MD USA (Presentation Abstract)
    ** Co-authored with Susan M. Abdel-Rahman, Matthew L. Breitkreutz, Brett J. Matzuka, Brian Rivera, Charlie Bi
  6. Dynamics of Cytosine Methylation in the Proximal Promoters of CYP3A4 and CYP3A7 in Pediatric and Prenatal Liver. Drug Metabolism and Disposition, [ PubMed ] (In Press)
    ** Co-authored with Carrie A. Vyhlidal, Charlie Bi, Shui Q. Ye, J. Steven Leeder
  7. A maximum likelihood framework for multiple sequence local alignment. IN: M Elloumi, CS Iliopoulos, JTL Wang and AY Zomaya (Editors) PATTERN RECOGNITION IN COMPUTATIONAL MOLECULAR BIOLOGY: TECHNIQUES AND APPROACHES, pp. 65-82 (Ch. 4) John Wiley & Sons Ltd. (2016) [Book Chapter]
  8. Design and Testing of an EHR-Embedded, Busulfan Pharmacokinetic Decision Support Tool for the Point-of-Care Clinician. Frontiers in Pharmacology, Frontier Pharmacol. 2016 Mar 30;7:65. doi: 10.3389/fphar.2016.00065. [ Frontiers | PubMed]
    ** Co-authored with Susan M. Abdel-Rahman, Matthew L. Breitkreutz, Charlie Bi, Brett J. Matzuka, Jignesh Dalal, K. Leigh Casey, Uttam Garg, Sarah Winkle, J. Steven Leeder, JeanAnn Breedlove, Brian Rivera

    [2015]

  9. Developmental changes in DNA methylation of CYP3A5 in human pediatric and prenatal liver 2015 ASPET at Experimental Biology (EB), March 28 - April 1, Boston, Massachusetts USA (Abstract)
    ** Co-authored with Carrie A. Vyhlidal, Charlie Bi, Roger Gaedigk, Dmitry Grigoryev, Shui Q. Ye, Stephen Kingsmore, J. Steven Leeder
  10. Methylome-seq Data Analysis. IN: S.Q. Ye (Editor) Big Data Analyses for Bioinformatics and Biomedical Discoveries, pp. 131-146 (Ch. 8) CRC Press/Taylor & Francis Group (2015) [Book Chapter]

    [2014]

  11. Dynamics of DNA methylation of human CYP3A gene promoters in pediatric liver 2014 Annual Meeting of The American Society for Pharmacology and Experimental Therapeutics (ASPET) at Experimental Biology (EB), April 26-30, San Diego, California USA (Abstract)
    ** Co-authored with Carrie A. Vyhlidal, Charlie Bi and J. Steven Leeder

    [2013]

  12. Identification of endogenous biomarkers of CYP2D6 phenotype in the urinary metabolome of pediactric subjects. 2013 Annual Pediatric Pharmacogenomics and Personalized Medicine Conference, Kansas City, Missouri USA (Abstract) page 42
    ** Co-authored with J.C. Tay, L. Shireman, T. Senn, D. Beyer, T. Bammler, J.S. Leeder, R. Pearce, N. Ahlers, K. Wright, C. Bi, A. Gaedigk, K. Thummel and Y.S. Lin
  13. Motif Discovery through Memetic Computing. (Invited Speaker) In: 2013 X-GEN Congress & Expo: Cambridge Healthtech Institute's Fourth Annual Genomic Data Analysis: Sequencing's Strategic Step , San Diego, CA USA, March 18-20, 2013.
  14. Central nervous system lymphoma in immunocompetent patients: The North Shore-Long Island Jewish Health System experience. J Clin Neurosci. 2013 Jan;20(1):75-9 [ PubMed ]
    ** Co-authored with Zhang X, Chen QH, Farmer P, Nasim M, Demopoulos A, Devoe C, Ranjan T, Eisenberg MB, Schulder M, Li JY.

    [2012]

  15. Identifying CYP2D6 endogenous biomarkers using metabolomics. 2012 Annual Pediatric Pharmacogenomics and Personalized Medicine Conference, Kansas City, Missouri USA (Abstract) page 45
    ** Co-authored with Y.S. Lin, J.C. Tay, K. Thummel, D. Beyer, T. Bammler, R. Pearce, N. Ahlers, K. Wright, C. Bi, A. Gaedigk and J.S. Leeder
  16. Large-scale computation of pediatric growth percentiles with fuzzy logic justification of parameter selection. Proceedings of The 2012 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB). IEEE Press, Piscataway, NJ, pages 43-46 (2012). [ IEEE Xplore ]
    ** Joint work with Steve Leeder
  17. Memetic algorithms for de novo motif-finding in biomedical sequences. Artificial Intelligence in Medicine 56 (1), 1-17 (2012). [ PubMed | ScienceDirect ]

    [2011]

  18. The Xla (X-linked anemia) mouse: A transient neonatal anemia caused by a Gata1 splicing mutation.
    Blood, 118, 1366-1367 (2011) [ PubMed ]
    ** Joint work with K Miller, M Silvey, D Logsdon, F Balch, N Nsumu, I Sokolovsky, M Gibson, D Heruth, and RA White
  19. Derivation of minimum best sample size from microarray data Sets: A Monte Carlo approach. Proceedings of The 2011 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB). IEEE Press, Piscataway, NJ, pp. 129-134 (2011). [ IEEE Xplore ]
    ** Joint work with Mara Becker and Steve Leeder.
  20. Tackling the challenging motif problem through hybrid particle swarm optimized alignment clustering. Proceedings of The 2011 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB). IEEE Press, Piscataway, NJ, pp. 84-89 (2011) [ IEEE Xplore ]
    ***Winner of Best Paper Award received from The 2011 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2011, Paris, France).

    [2010]

  21. Allele drop-out in the MECP2 gene due to G-quadruplex and i-motif sequences when using PCR-based diagnosis for Rett syndrome. Genetic Testing and Molecular Biomarkers, 14 (2), 241-247 (2010). [ PubMed ]
  22. Determinisitc local alignment methods improved by a simple genetic algorithm. Neurocomputing, 73, 2394-2406 (2010). [ ScienceDirect | ACM Digital Library ]
  23. Supervised learning of maternal cigarette-smoking signatures from placental gene expression data: A case study. Proc. 2010 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB), Montreal, Canada, pp. 1-6 (2010). (with Carrie Vyhlidal and Steve Leeder) [ IEEEXplore ]
  24. Comparison of optimization techniques for sequence pattern discovery by maximum-likelihood. Pattern Recognition Letters, 31, 2147-2160 (2010). [ ScienceDirect | ACM Digital Library ]

    [2009]

  25. A Monte Carlo EM algorithm for motif discovery in biomolecular sequences. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6 (3), 370-386 (2009). [ PubMed ]
  26. DNA motif alignment by evolving a population of Markov chains. BMC Bioinformatics, 10, S13 (2009). [ PubMed | PDF ]
  27. Genome-wide screening SNPs with arginine vs tryptophan change associated with allergy. Journal of Allergy and Clinical Immunology, 123, S167 (2009).
    ** Joint work with J Meng and LJ Rosenwasser
  28. DNA motif alignment by evolving a population of Markov chains. Proc. the 7th Asia-Pacific Bioinformatics Conference ,vol 7, pp. 126-137. Tsinghua University Press, Beijing, CHINA (2009) [book chapter]

    [2008]

  29. Data augmentation algorithms for detecting conserved domains in protein sequences: A comparative study. Journal of Proteome Research, 7 (1), 192-201 (2008) [ PubMed ]
  30. A comparative study on structured motif detection: algorithms and applications. Molecular Pharmaceutics, 5 (1), 3-16 (2008) [ PubMed ]
  31. Computational intelligence in multiple sequence alignment. Intl. J. Intelligent Computing and Cybernetics, 1 (1), 8-24 (2008)
  32. Evolutionary Metropolis sampling in sequence alignment space. Proc. 2008 IEEE Congress on Evolutionary Computation (CEC), Hong Kong, CHINA, pp. 189-194 (2008) [ IEEEXplore ]
  33. Neuro-Fuzzy classification of the Rhagoletis pomonella species group using digitized wing structure. Proc. 2008 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB), Idaho, USA, pp. 159-165 (2008) [ IEEEXplore ]

    [2007]

  34. SEAM: A stochastic EM-type algorithm for motif-finding in biopolymer sequences. Journal of Bioinformatics and Computational Biology, 5 (1), 47-77 (2007) [ PubMed ]
  35. Wing pattern-based classification of the Rhagoletis pomonella species complex using genetic neural networks. Intl J. Computer Sci. & Appl., 4 (3), 1-14 (2007) [ PDF ]
  36. A genetic-based EM motif-finding algorithm for biological sequence analysis. Proc. 2007 IEEE Computational Intelligence Symposium on Bioinformatics & Computational Biology (CIBCB), pp. 275-282, Hawaii, USA (2007) [ IEEEXplore ]
    *** Winner of Best Overall Paper Award received from IEEE SSCI'2007.
  37. A survey of in silico motif discovery and computational intelligence applications. Proc. 2007 International Conference on Artificial Intelligence, pp. 147-153. Las Vegas, USA. CSREA Press
  38. Multiple sequence local alignment using Monte Carlo EM algorithm. Lecture Notes in Bioinformatics, vol 4463, pp. 465-476, Springer-Verlag (2007) [ Book Chapter ]

    [2006]

  39. Correlation between scaffold/matrix attachment region (S/MAR) binding activity and DNA duplex Destabilization energy. Journal of Molecular Biology, 358 (2), 597-613 (2006) [ PubMed | PDF ]
  40. BIPAD: A web server for modeling bipartite sequence elements. BMC Bioinformaitcs, 7:76 (2006) [ PubMed | PDF ]
  41. Computational model of the antioxidant response element. ISSX-2006 (abstract)
  42. A Monte Carlo EM algorithm for motif discovery problem. Proceedings of 2006 ISMB Bioinformatics Rocky Conference, Snowmass/Aspen, CO, USA (abstract)

    [2005]

  43. Information theory as a model of genomic sequences. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics, vol 7, pp. 2868-2880, John Wiley & Sons Ltd. (2005) [ Book Chapter ]
  44. Determining thresholds for binding site sequence models using information theory. Proc. 6th International Symposium on Computational Biology and Genome Informatics, pp. 1285-1290. Utah, USA (2005)

    [2004]

  45. The analysis of stress-induced duplex destabilization in long genomic DNA sequences. Journal of Computational Biology, 11 (4), 519-543 (2004) [ PubMed | PDF ]
  46. Bipartite pattern discovery by entropy minimization-based multiple local alignment. Nucleic Acids Research, 32 (17), 4979-4991 (2004) [ PubMed | PDF ]
  47. WebSIDD: Server for prediction of the stress-induced duplex destabilized (SIDD) sites in superhelical DNA. Bioinformatics, 20 (9), 1477-1479 (2004) [ PubMed | PDF ]
  48. A minimization entropy-based bipartite algorithm with application to PXR/RXRa binding sites. Proc. 8th Ann. Conference on Research in Computational Molecular Biology (RECOMB) , San Diego, California USA, pp. 453-454 (2004)

    [2003]

  49. The approximate algorithm for analysis of the strand separation transition in superhelical DNA using nearest neighbor energetics. Proc. IEEE Computer Society for Bioinformatics, pp. 460-461. Stanford University, California USA. IEEE Publisher. (2003) [ IEEEXplore ]

    [2002]

  50. Pattern Classification of the Rhagoletis pomonella Species Complex.
    Ph.D. Dissertation: Graduate School of The Pennsylvania State University, University Park, PA, USA.

Last modified: January 13, 2016