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Table 3: List of the most frequently appearing genes among signi cant gene pairs in a cluster, with an abrupt positive association change from dysplastic nodule to hepatocellular carcinoma grade I.

in Statistical Inference Methods for Detecting Altered Gene Associations
by Sang-Heon Yoon, Je-Suk Kim, Hae-hiang Song
"... In PAGE 8: ... We analyzed, among the general cluster patterns that were revealed, the speci c clusters of interest; that is, not the clusters which show a high correlation throughout di erent stages of disease, or clusters which show up-and-down cyclic changes, but in particular, pro les of correlation changes from no association to high association. Table3 presents a list of the most frequently appearing genes among signi cant gene-pairs in a cluster, with a positive-association change from a dysplastic nodule to hepatocellular carcinoma grade I. The subset of genes suggests that the association change with tumor grade might be correlated with the transition from pre-invasive to invasive growth.... In PAGE 8: ... The subset of genes suggests that the association change with tumor grade might be correlated with the transition from pre-invasive to invasive growth. Several genes of Table3 were already known to be involved in liver carcinogenesis or were studied in pharmacogenetics. SULT2A1 is one of the frequently mentioned genes, and two example pairs of genes with SULT2A1 are shown in Fig.... ..."

TABLE 1. Changes in predictive values as a function of the prevalence of the value assigned to a variable in a US cohort of stage I and II breast cancer patients diagnosed between 1990 and 1994*

in unknown title
by unknown authors 2006

Table 1 Results of the analysis of the disease free survival data of the patients included in the breast cancer trial (standard error in parentheses)

in Comparison of different estimation procedures for proportional hazards model with random effects
by José Cortiñas Abrahantes , Catherine Legrand, Tomasz Burzykowski , Paul Janssen , Vincent Ducrocq , Luc Duchateau 2006
"... In PAGE 10: ... The model will be fitted to the data using each of the four estimation methods reviewed in Section 3. The results of the four estimation methods are shown in Table1 . All the methods produce similar point estimates, consistently yielding a very small estimate (almost 0) for the variance of the random treatment effects.... ..."

Table 1: Selection of independent variables. All models include the classical risk factors (age, menopausal status, age at menarche, familial BC, history of benign breast disease). Model alc alc0 tfat tsat

in Model Selection for Generalized Linear Models via GLIB, with Application to Epidemiology
by Adrian E. Raftery, Sylvia Richardson
"... In PAGE 27: ... The models to be t are speci ed by the input design matrix x and the input matrix models, which speci es the subsets to be considered. Columns 2{5 of Table1 constitute an example of the input models matrix. 6 Discussion We have described a Bayesian model-building strategy for generalized linear models that avoids the di culties of commonly-used ad-hoc strategies, namely arbitrariness in the cod- ing of risk factors, lack of knowledge of the overall properties of model selection strategies based on signi cance tests, and failure to account for model uncertainty.... ..."

TABLE 2. Portfolio of proposed clinical trials in breast cancer evaluating hypotheses about systemic disease regulatory effects of surgical oophorectomy in the luteal phase of the menstrual cycle (Love and Niederhuber)

in Annals of Surgical Oncology, 11(9):818–828 DOI: 10.1245/ASO.2004.02.019 Educational Review Models of Breast Cancer Growth and Investigations of Adjuvant
by Surgical Oophorectomy, Richard R. Love, John E. Niederhuber 2004

Table 8.2 presents age-adjusted mortality rates for chronic diseases associated with sedentary lifestyle in U.S. women by race and ethnicity. Coronary heart disease (CHD) and cerebrovascular disease (stroke) are the two leading causes of death in all five population groups. Diabetes ranks as the third leading cause of death from chronic disease in black, Hispanic, Native American/Alaskan Native, and Asian/Pacific Islander women (exceeding death rates from lung cancer, breast cancer, chronic obstructive pulmonary disease, and colorectal cancer) (Centers for Disease Control, 1994).

in Physical Activity and Women's Health Ch ristine L. W ells ARIZONA STATE UNIVERS ITY A NOTE FROM THE ED ITOR S
by Originally Published As, Ch Ristine L. W Ells

Table 3. Functional characteristics of genes in recurrent amplicons associated with reduced survival duration in breast cancer

in E.: “A Summary of
by Koei Chin, Y Devries, Jane Fridly, Paul T. Spellman, Ritu Roydasgupta, Wen-lin Kuo, Anna Lapuk, Richard M. Neve, Zuwei Qian, Tom Ryder, Fanqing Chen, Heidi Feiler, Taku Tokuyasu, Chris Kingsley, Shanaz Dairkee, Zhenhang Meng, Karen Chew, Daniel Pinkel, Ajay Jain, Britt Marie Ljung, Laura Esserman, Donna G. Albertson, Frederic M. Waldman, Joe W. Gray 1968
"... In PAGE 3: ...es (Hyman et al., 2002; Pollack et al., 1999). We tested associ- ations between copy number and expression level for 186 genes in regions of amplification at 8p11-12, 11q13-q14, 17q11-12, and 20q13, and we identified 66 genes in these regions whose expression levels were correlated with copy number (FDR lt; 0.01, Wilcoxon rank-sum test; Table3 ). These genes define the transcriptionally important extents of the regions of recurrent amplification.... In PAGE 5: ... Considering the strong association between amplification and outcome, we explored the possibility that some of these genes were overexpressed in tumors in which they were not amplified and that overexpression was associated with reduced survival duration in those tumors. Increased expression levels of seven genes (see Table3 ) were associated with reduced survival or distant recurrence at the p lt; 0.1 level, but only two, the growth factor receptor-binding protein GRB7 (17q) and the keratin-as- sociated protein KTRAP5-9 (11q), at the p lt; 0.... In PAGE 9: ... Table3 . Continued Gene Ch Mbp p value, amplification p value, disease free survival p value, distant recurrence Transcript description Cancer function reference Kbp to site of viral integration Druggable? ACACA 17 35.... ..."
Cited by 1

Table 9 shows that for the wisconsin breast cancer data set, class 1 is probably compact since SCAD2-CA FFnds a single prototype in all four jackknives. On the

in
by Hichem Frigui, Olfa Nasraoui 2003
"... In PAGE 12: ... This conFFrms the importance of the unsupervised feature weighting mechanism of SCAD2. For instance, the improvement in the correct classiFFcation rate of the wis- consin breast cancer data set is small, as expected, because the feature weights do not vary widely as can be seen in Table9 . On the other hand, a signiFFcant improvement can be observed for the heart disease data set because the feature weights determined by SCAD2-CA vary widely as shown in Table 10.... ..."

TABLE 2 Summary of Results

in Results of Preliminary Clinical Trials of the Positron Emission Mammography System PEM-I: A Dedicated Breast Imaging System Producing Glucose Metabolic Images Using FDG
by Kavita Murthy, Marianne Aznar, Christopher J. Thompson, Antoine Loutfi, Robert Lisbona, Jean H. Gagnon 2000
Cited by 1

Table 9. On the other hand, a signiFFcant improvement can be observed for the heart disease data set because the feature weights determined by SCAD2-CA vary widely as shown in Table 10.

in
by Hichem Frigui, Olfa Nasraoui 2003
"... In PAGE 13: ...05 0.03 Table9 shows that for the wisconsin breast cancer data set, class 1 is probably compact since SCAD2-CA FFnds a single prototype in all four jackknives. On the other hand, class 2 may have a more complex distribu- tion since it gets split into two clusters in all but one... ..."
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