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Articles 31 - 34 of 34
Full-Text Articles in Biostatistics
The Sensitivity And Specificity Of Markers For Event Times, Tianxi Cai, Margaret S. Pepe, Thomas Lumley, Yingye Zheng, Nancy Swords Jenny
The Sensitivity And Specificity Of Markers For Event Times, Tianxi Cai, Margaret S. Pepe, Thomas Lumley, Yingye Zheng, Nancy Swords Jenny
Harvard University Biostatistics Working Paper Series
No abstract provided.
New Confidence Intervals For The Difference Between Two Sensitivities At A Fixed Level Of Specificity, Gengsheng Qin, Yu-Sheng Hsu, Xiao-Hua Zhou
New Confidence Intervals For The Difference Between Two Sensitivities At A Fixed Level Of Specificity, Gengsheng Qin, Yu-Sheng Hsu, Xiao-Hua Zhou
UW Biostatistics Working Paper Series
For two continuous-scale diagnostic tests, it is of interest to compare their sensitivities at a predetermined level of specificity. In this paper we propose three new intervals for the difference between two sensitivities at a fixed level of specificity. These intervals are easy to compute. We also conduct simulation studies to compare the relative performance of the new intervals with the existing normal approximation based interval proposed by Wieand et al (1989). Our simulation results show that the newly proposed intervals perform better than the existing normal approximation based interval in terms of coverage accuracy and interval length.
A Causal Inference Approach For Constructing Transcriptional Regulatory Networks, Biao Xing, Mark J. Van Der Laan
A Causal Inference Approach For Constructing Transcriptional Regulatory Networks, Biao Xing, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
Transcriptional regulatory networks specify the interactions among regulatory genes and between regulatory genes and their target genes. Discovering transcriptional regulatory networks helps us to understand the underlying mechanism of complex cellular processes and responses. In this paper, we describe a causal inference approach for constructing transcriptional regulatory networks using gene expression data, promoter sequences and information on transcription factor binding sites. The method rst identies active transcription factors under each individual experiment using a feature selection approach similar to Bussemaker et al. (2001), Keles et al. (2002) and Conlon et al. (2003). Transcription factors are viewed as `treatments' and gene …
2d Quantitative Structure Activity Relationship Modeling Of Methylphenidate Analogues Using Algorithm And Partial Least Square Regression, Noureen Wadhwaniya
2d Quantitative Structure Activity Relationship Modeling Of Methylphenidate Analogues Using Algorithm And Partial Least Square Regression, Noureen Wadhwaniya
Theses
Quantitative Structure-Activity Relationship (QSAR) analysis attempts to develop a predictive model of biological activity based on molecular descriptors. 2D QSAR uses descriptors, such as topological indices, that are independent of molecular conformation. A genetic algorithm - partial least squares (GA-PLS) approach was used to identify the molecular descriptors that correlate to the biological activity (binding affinity) of a set of 80 methylphenidate analogues and to construct a predictive model. The GA code was implemented using the fitness function (1-(n-1)(1-q2)/ (n - c)), where n is the number of compounds, c is the optimal number of components, and q …