the pairwise 2-class classification models, and the accumulated AUC represents the multiclass perf<strong>or</strong>mance [3, 10, 13, 14]. The weighting scheme was as follows: AUC = % auc * (1- (Ci/T))/n-1, (4) where C is the class numbers, T is the sample numbers, and n is the number <strong>of</strong> classes. The weighting scheme was chosen over the average AUC, to compensate f<strong>or</strong> the large class bias. Classifying the adenocarcinoma samples with little classification ability f<strong>or</strong> the smaller classes yielded an inflated model AUC. Results Eighteen genes are implicated f<strong>or</strong> differentiating NSCLC when the gain criterion threshold is set at 0.8. These ProbeSets are provided in Table 4.1, along with their HUGO identification, chromosome location, the calculated gain ration and the GO processes. Investigation <strong>of</strong> the gene’s GO processes includes cell proliferation, mitotic cell cycle control, cell motility and adhesion, inflammat<strong>or</strong>y response, signal transduction, and cell programmed death. 118
119 Table 5.1: : NSCLC candidate genes. The list <strong>of</strong> 18 genes from the Bhattacharjee NSCLC dataset, as down selected using the gain criteria. *The probes from probeset_id, 576_at, measure the chromosome 7 transcript region 150,342,056-150,342,499, which has overlapping opposed sense genes f<strong>or</strong> ATG9B (ATG9 autophagy related 9 homolog B) and NOS3 (nitric oxide synthase 3 -endothelial cell) Probeset_id 40841_at 34294_at 39631_at 576_at* 576_at* 37004_at 39016_r_at 39066_at 1718_at 33756_at 32052_at 33323_r_at 37009_at 36495_at 34301_r_at 32680_at 41639_at 654_at Gene_id Chromosome Gain GO process TACC1 8 1.018 Cell cycle, cell division KIFC3 16 0.992 Golgi <strong>or</strong>ganization and biogenesis, microtubule-based movement, visual perception EMP2 16 0.988 cell proliferation ATG9B 7 0.957 autophagic vacuole f<strong>or</strong>mation, autophagy angiogenesis, cell motility, learning, lipopolysaccharide-mediated signaling pathway, lung development, negative regulation <strong>of</strong> calcium ion transp<strong>or</strong>t, negative regulation <strong>of</strong> hydrolase activity, negative regulation <strong>of</strong> potassium ion transp<strong>or</strong>t, negative regulation <strong>of</strong> smooth muscle cell proliferation, nitric oxide biosynthetic process, ovulation from ovarian follicle, oxidation reduction, regulation <strong>of</strong> NOS3 7 0.957 sodium ion transp<strong>or</strong>t, signal transduction lipid metabolic process, <strong>or</strong>gan m<strong>or</strong>phogenesis, regulation <strong>of</strong> liquid surface tension, respirat<strong>or</strong>y gaseous SFTPB 2 0.954 exchange, sphingolipid metabolic process KRT6A 12 0.935 cell differentiation, ectoderm development, positive regulation <strong>of</strong> cell proliferation MFAP4 17 0.920 cell adhesion, signal transduction ARPC2 2 0.894 cell motility, regulation <strong>of</strong> actin filament polymerization AOC3 17 0.883 amine metabolic process, cell adhesion, inflammat<strong>or</strong>y response, oxidation reduction KRT121P 11 0.861 keratin 121 pseudogene DNA damage response, signal transduction resulting in induction <strong>of</strong> apoptosis, apoptotic program, cell proliferation, keratinocyte differentiation, negative regulation <strong>of</strong> caspase activity, negative regulation <strong>of</strong> protein kinase activity, regulation <strong>of</strong> cyclin-dependent protein kinase activity, release <strong>of</strong> cytochrome c SFN 1 0.858 from mitochondria, signal transduction, skin development UV protection, hydrogen peroxide catabolic process, negative regulation <strong>of</strong> apoptosis, oxidation CAT 11 0.855 reduction, protein tetramerization, response to reactive oxygen species FBP1 9 0.842 carbohydrate metabolic process, fructose metabolic process, gluconeogenesis KRT17 17 0.841 biological_process, epidermis development TNIK 3 0.832 JNK cascade, protein amino acid phosph<strong>or</strong>ylation, protein kinase cascade, response to stress NCAPH 2 0.832 cell division, mitosis, mitotic cell cycle, mitotic chromosome condensation cytoplasmic sequestering <strong>of</strong> transcription fact<strong>or</strong>, negative regulation <strong>of</strong> cell proliferation, regulation <strong>of</strong> MXI1 10 0.825 transcription, regulation <strong>of</strong> transcription, DNA-dependent
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An Adenocarcinoma Case Study of the
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DEDICATION The work presented in th
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TABLE OF CONTENTS LIST OF TABLES ..
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Conclusion.........................
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LIST OF FIGURES Figure Page Figure
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violate the linear correlation rela
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Chapter 1: An Introduction to Micro
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previously stated, rigorous reagent
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Factors influencing Signal Interpre
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likelihood that no such structural
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hybridization and multiple dye stra
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classical reaction equations, modif
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prevent the hybridization of probes
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platforms are used to deposit them
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and chip layout [64]. In particular
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whether analyses based upon individ
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The process of determining a candid
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implemented in order to demonstrate
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affecting probe-target duplex forma
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It has long been known that the var
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probes can thus be reincorporated i
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(Carr, ms in review). This ProbeFAT
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have specific attributes which can
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elow saturation. The investigator m
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a. A filter based on how many probe
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means. The remaining sets possess s
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for the 24 samples in the Lu, et al
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Table 2.1: Probe Numbers per filter
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the effect can be. Both the type of
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described above. In Figure 2.3, the
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various data processing stages are
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position of the probe on the transc
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Figure 2.5: BaFL consistency. Demon
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Figure 2.6: Probe-Transcript region
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Table 2.3: ProbeSet behavior predic
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cleansing process. This is demonstr
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Table 2.4: ProbeSet behavior of pro
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A Priori Prediction We demonstrated
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Conclusion We have presented a comp
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- Page 143 and 144: Appendix A # This is the main drive
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- Page 147 and 148: def DriverXH(usr, pswd, db, logfile
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- Page 151 and 152: #determine outliers lowrs1=nonzero(
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- Page 159 and 160: Appendix E # The result of permutin
- Page 161 and 162: BIBLIOGRAPHY 149
- Page 163 and 164: 13. Bowtell DD: Options available--
- Page 165 and 166: method addressing dye, intensity-de
- Page 167 and 168: 73. Alter O, Brown PO, Botstein D:
- Page 169 and 170: 11. Kumari S, Verma LK, Weller JW:
- Page 171 and 172: 38. Michael Stonebraker LAR, Michae
- Page 173 and 174: 64. Cropp CS, Lidereau R, Leone A,
- Page 175 and 176: 15. Irizarry RA: affy. In.: Biocond
- Page 177 and 178: Chapter 4: 1. Minna JD, Roth JA, Ga
- Page 179 and 180: 30. Delaval B, Ferrand A, Conte N,
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27. Bai J, Cederbaum AI: Catalase p
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51. Shouse GP, Cai X, Liu X: Serine