Target Discovery and Validation Reviews and Protocols

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Gene Target Discovery 121 There is no doubt that a band pattern showing potentially differentially expressed transcripts may be obtained in a short time. However, the most timeconsuming and problematic step in the overall DD technique is the confirmation that the isolated cDNA clone represents a differentially expressed gene. This problem has led to a multitude of publications reporting improvements and simplification of the basic protocol to reduce the high frequency of false positives and to confirm the differential expression pattern of selected candidates (27–30). A high rate of false positives and time-consuming effort to find the true positives have been the main drawbacks with this method (31,32). In addition, rare transcripts are difficult to detect. The advances are the experimental simplicity by which candidates are obtained, the ability to use as little as a few nanograms of starting material (33), and the possibility to identify novel transcripts. 1.2. Global Techniques Global cDNA techniques analyze the total or large parts of the mRNA populations in a single assay. The aim may be to quantitatively estimate the number of expressed genes in a defined biological material, estimate their absolute or relative abundance levels, survey global changes in gene expression patterns in response to extrinsic and intrinsic factors, identify specific genes whose expression is altered because of such factors, or simply to identify as many as possible of the genes expressed in a defined biological material. This process may or may not include differentially expressed, novel as well as known genes. Because of the unstable nature of RNA, the mRNA populations are usually reverse transcribed into DNA complementary to the RNA strand (cDNA), which in theory has the same distribution as the original mRNA populations. It is the populations of cDNA that normally are the subjects of investigation. 1.2.1. Large-Scale Sequencing of Expressed Sequence Tag (EST) Sequences ESTs are segments of sequences from cDNA clones that correspond to mRNA. The tags can thus be used to identify transcripts in a specific tissue. Adams and co-workers coined the term EST in 1991, when the first high-throughput sequencing of a cDNA library was reported (34). The clones are randomly picked and either randomly single-pass sequenced, or more commonly, sequenced from the 5′ or 3′ ends or both, to generate on average a 200- to 700-bp sequence. Even much smaller segments are sufficient for rapid identification of expressed genes by sequence analysis. The initial objective of EST sequencing was to speed up the process of gene identification and possible splicing alternative events (35). In addition, large-scale sequencing of EST sequences has proven to be
122 Røsok and Sioud a powerful approach to discover novel genes and for transcript profiling (36). By comparing the transcription profiles from cDNA libraries representing different tissues, differently expressed genes may be identified. However, because several tissues are represented by low numbers of clones (
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METHODS IN MOLECULAR BIOLOGY 360 T
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M E T H O D S I N M O L E C U L A R
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© 2007 Humana Press Inc. 999 River
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vi Preface get. Approaches to targe
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viii Contents 10 Transgenic Animal
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x Contributors SAHOHIME MATSUMOTO
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xii Contents of Volume 2 12 Validat
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2 Sioud disease pathogenesis and pe
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4 Sioud A more fruitful approach fo
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6 Sioud both transient and permanen
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8 Sioud serum biomarkers. This syne
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10 Sioud Fig. 2. Schematic of targe
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12 Sioud 13. Magin, T. M. (1998) Le
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Harnessing the Human Genome 15 The
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Harnessing the Human Genome 17 Fig.
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Harnessing the Human Genome 23 The
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Harnessing the Human Genome 27 repr
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Harnessing the Human Genome 29 14.
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Harnessing the Human Genome 31 45.
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34 Imoto et al. (4,5), and Bayesian
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36 Imoto et al. 2. Materials Two ty
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38 Imoto et al. Fig. 3. Graphical v
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40 Imoto et al. Fig. 5. Result of t
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42 Imoto et al. p(D |G) = ∫ p(D,
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44 Imoto et al. β k (k = 1,…,q j
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46 Imoto et al. Fig. 7. Partial res
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48 Imoto et al. Fig. 8. Strategy to
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50 Imoto et al. Fig. 9. (continued)
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52 Imoto et al. Table 3 List of Roo
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54 Imoto et al. 5. De Hoon, M. J. L
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56 Imoto et al. 39. Kamimura, T., S
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58 Beaty et al. cytotoxic drugs and
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60 Beaty et al. Fig. 1. Principles
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62 Beaty et al. oligonucleotide mic
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64 Beaty et al. 3. The 12% polyacry
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66 Beaty et al. 2.3.3. Protein Stai
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68 Beaty et al. 3.1.3. Labeling of
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172 Houdebine 2.2.3. Knock-In Into
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174 Houdebine as insulators. The co
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176 Houdebine Fig. 5. Different met
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178 Houdebine systems. Moreover, st
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180 Houdebine contribute to generat
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182 Houdebine Fig.7. Example of a v
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184 Houdebine more extensively. Tra
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186 Houdebine and stroma. Several o
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188 Houdebine explained at the mole
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190 Houdebine of the intestinal epi
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192 Houdebine interference of the g
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194 Houdebine 17. Whitelaw, C. B. A
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196 Houdebine 51. Bell, A. C., West
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198 Houdebine 86. Carmichael, G. G.
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200 Houdebine 121. Pailhoux, E., Vi
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202 Houdebine 156. Auerbach, A. B.,
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204 Vijayaraj, Söhl, and Magin 1.
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206 Vijayaraj, Söhl, and Magin Fig
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208 Vijayaraj, Söhl, and Magin fil
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210 Table 1 Orthologous Human and M
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212 Table 2 Orthologous Human and M
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214 Vijayaraj, Söhl, and Magin ulc
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222 Vijayaraj, Söhl, and Magin 1.2
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226 Vijayaraj, Söhl, and Magin gen
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230 Vijayaraj, Söhl, and Magin f.
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234 Vijayaraj, Söhl, and Magin b.
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240 Vijayaraj, Söhl, and Magin alt
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242 Table 3 Time Schedule For Aggre
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250 Vijayaraj, Söhl, and Magin 101
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12 The HUVEC/Matrigel Assay An In V
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256 Skovseth, Küchler, and Haralds
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270 Iversen and Sørensen witnessed
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272 Iversen and Sørensen Fig. 1. P
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274 Iversen and Sørensen the core
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14 An Overview of the Immune System
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Overview of Immune System 279 diffe
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Overview of Immune System 281 Fig.
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Overview of Immune System 283 then
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Overview of Immune System 285 expre
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Overview of Immune System 287 Once
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Overview of Immune System 289 solub
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Overview of Immune System 291 amino
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Overview of Immune System 293 (unre
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Overview of Immune System 297 the c
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Overview of Immune System 299 (44).
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Overview of Immune System 301 demon
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Overview of Immune System 307 some
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Overview of Immune System 309 sera
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Overview of Immune System 313 measu
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Overview of Immune System 315 42. H
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Overview of Immune System 317 74. D
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15 Potential Target Antigens for Im
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Tumor Antigen Discovery 321 develop
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Tumor Antigen Discovery 323 panel b
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Tumor Antigen Discovery 325 16. Joc
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16 Identification of Tumor Antigens
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Immunoproteomics 329 by “shot gun
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Immunoproteomics 331 isoelectric fo
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Immunoproteomics 333 3. 2D-PAGE is
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17 Protein Arrays A Versatile Toolb
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Protein Arrays 337 Table 1 Classifi
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Protein Arrays 339 fractions from c
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Protein Arrays 341 combinatorial sc
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Protein Arrays 343 The ideal proteo
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Protein Arrays 345 18. Cekaite, H.
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Protein Arrays 347 49. Yuko Kawahas
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Index 349 Index A Acetyl-CoA carbox
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Index 351 conditional by using FRT
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Index 353 Recombinant tumor antigen
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