The construction and assessment of a statistical model for the prediction of protein assay data

Jennifer Pittman, J. Sacks, S. Stanley Young

Research output: Contribution to journalArticle

2 Scopus citations


The focus of this work is the development of a statistical model for a bioinformatics database whose distinctive structure makes model assessment an interesting and challenging problem. The key components of the statistical methodology, including a fast approximation to the singular value decomposition and the use of adaptive spline modeling and tree-based methods, are described, and preliminary results are presented. These results are shown to compare favorably to selected results achieved using comparitive methods. An attempt to determine the predictive ability of the model through the use of cross-validation experiments is discussed. In conclusion a synopsis of the results of these experiments and their implications for the analysis of bioinformatic databases in general is presented.

Original languageEnglish (US)
Pages (from-to)729-741
Number of pages13
JournalJournal of Chemical Information and Computer Sciences
Issue number3
Publication statusPublished - May 1 2002


ASJC Scopus subject areas

  • Chemistry(all)
  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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