Publications

Displaying 601 - 602 of 602
  • Ziegler, A., DeStefano, A. L., König, I. R., Bardel, C., Brinza, D., Bull, S., Cai, Z., Glaser, B., Jiang, W., Lee, K. E., Li, C. X., Li, J., Li, X., Majoram, P., Meng, Y., Nicodemus, K. K., Platt, A., Schwarz, D. F., Shi, W., Shugart, Y. Y. and 7 moreZiegler, A., DeStefano, A. L., König, I. R., Bardel, C., Brinza, D., Bull, S., Cai, Z., Glaser, B., Jiang, W., Lee, K. E., Li, C. X., Li, J., Li, X., Majoram, P., Meng, Y., Nicodemus, K. K., Platt, A., Schwarz, D. F., Shi, W., Shugart, Y. Y., Stassen, H. H., Sun, Y. V., Won, S., Wang, W., Wahba, G., Zagaar, U. A., & Zhao, Z. (2007). Data mining, neural nets, trees–problems 2 and 3 of Genetic Analysis Workshop 15. Genetic Epidemiology, 31(Suppl 1), S51-S60. doi:10.1002/gepi.20280.

    Abstract

    Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.
  • Zwitserlood, I. (2003). Classifying hand configurations in Nederlandse Gebarentaal (Sign Language of the Netherlands). PhD Thesis, LOT, Utrecht. Retrieved from http://igitur-archive.library.uu.nl/dissertations/2003-0717-122837/UUindex.html.

    Abstract

    This study investigates the morphological and morphosyntactic characteristics of hand configurations in signs, particularly in Nederlandse Gebarentaal (NGT). The literature on sign languages in general acknowledges that hand configurations can function as morphemes, more specifically as classifiers , in a subset of signs: verbs expressing the motion, location, and existence of referents (VELMs). These verbs are considered the output of productive sign formation processes. In contrast, other signs in which similar hand configurations appear ( iconic or motivated signs) have been considered to be lexicalized signs, not involving productive processes. This research report shows that meaningful hand configurations have (at least) two very different functions in the grammar of NGT (and presumably in other sign languages, too). First, they are agreement markers on VELMs, and hence are functional elements. Second, they are roots in motivated signs, and thus lexical elements. The latter signs are analysed as root compounds and are formed from various roots by productive processes. The similarities in surface form and differences in morphosyntactic characteristics observed in comparison of VELMs and root compounds are attributed to their different structures and to the sign language interface between grammar and phonetic form

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