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Table 1 (Continued)Server name URL Approach ReferencesPreLink http://genomics.eu.org/spip/PreLink Rule-based. Ratio of multinomial probabil- 76ities (for linker and structured regions)combined with the distance to the nearesthydrophobic clusterRONN http://www.strubi. Feed-forward neural network in the space 75ox.ac.uk/RONN of distances to a set of prototypesequences of known fold stateDISpro http://www.igb.uci.edu/servers/psss.html Recursive neural network based on 77sequence profiles, predicted secondarystructure and relative solventaccessibilityVSL http://www.ist.temple.edu/ Logistic regression (VSL1) and linear 78,79disprot/predictorVSL2.php support vector machine (VSL2)based on sequence composition,physicochemical properties, andprofiles. Combination of shortand long disorder predictorsDRIP-PRED http://www.sbc.su.se/~maccallr/ Kohonen’s self-organizing maps based –disorder/ on sequence profilesSPRITZ http://protein.cribi.unipd.it/spritz/ Nonlinear support vector machine based 80on multiply aligned sequences. Separatepredictors for short and long disorderregions74
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Gene Function Analysis
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METHODS IN MOLECULAR BIOLOGYGene Fu
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PrefaceThis volume of Methods in Mo
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Prefaceixcolleagues demonstrate how
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xiiContentsPART III EXPERIMENTAL ME
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ICOMPUTATIONAL METHODS I
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4 BidautTable 1Input File Format Us
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6 BidautTable 2Folder Layout to Use
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8 Bidaut• alphaA: this is the num
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10 Bidautcomputing the maximum corr
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12 BidautFig. 3. The complete Clutr
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Table 3Some Identified Patterns (5,
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16 BidautFig. 4. This is a comparis
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18 BidautReferences1. Hughes, T. R.
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20 Kirov et al.way to associate gen
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22 Kirov et al.based on a study ass
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24 Kirov et al.1. Retrieve the gene
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26Fig. 1. Functional associations f
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28 Kirov et al.Fig. 2. Pathway anal
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30 Kirov et al.3. Gene symbols usag
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32 Kirov et al.9. OBO_Team, Open Bi
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3Estimating Gene Function With Leas
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Estimating Gene Function With LS-NM
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Page 122: 50 Gonye et al.activity and problem
Page 126: 52 Gonye et al.Currently, PAINT can
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Page 186: 82 Uversky et al.the box Raw Output
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Page 198: 88 Uversky et al.13. Uversky, V. N.
Page 202: 90 Uversky et al.50. Vucetic, S., O
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Sybil: Multiple Genome Comparison a
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7Estimating Protein Function Using
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Estimating Protein Function Using P
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130 Davuluriinteracting proteins an
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Table 1Web URLs of Promoter, TF Dat
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134 DavuluriPWM-based models do not
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136 DavuluriTF-map alignments of or
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138 Davuluridiscussed which program
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140 DavuluriTable 2ER-a-Responsive
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Table 3Sample Data Matrix Represent
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Table 3 (Continued)Class MYCMAX MYC
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146 DavuluriFig. 3. (A) CART Tree:
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148 Davuluri11. Vlieghe, D., Sandel
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150 Davuluri44. Berezikov, E., Gury
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9Mining Biomedical Data Using MetaM
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Mining Biomedical Data Using MMTx a
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172 Ho et al.Fig. 1. Artificial exa
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174 Ho et al.allowing for cases whe
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176 Ho et al.A different measure is
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178 Ho et al.3.1.3. LA and Generali
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180 Ho et al.The ECF-statistic can
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182 Ho et al.In the special case of
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184 Ho et al.Fig. 5. An illustratio
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186 Ho et al.Fig. 7. The power curv
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188 Ho et al.this section were not
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190 Ho et al.References1. Schena, M
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IIIEXPERIMENTAL METHODS
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194 Caldwell et al.for sequences th
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196 Caldwell et al.query because it
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198 Caldwell et al.Fig. 1. (A) Prot
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200 Caldwell et al.outside primer o
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202 Caldwell et al.5. Targeting scr
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204 Caldwell et al.will allow the s
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206 Caldwell et al.3.1.6. Plasmid P
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208 Caldwell et al.PCR amplify the
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210 Caldwell et al.8. Thawing cells
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212 Zhang et al.Going one step beyo
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214 Zhang et al.Fig. 2. Generation
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216 Zhang et al.Perform PCR cycles,
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218 Zhang et al.Fig. 4. Schematic m
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220 Zhang et al.Fig. 5. Replacement
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13Construction of Simple and Effici
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DNA Vector-Based shRNA-Expression S
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244 Hust et al.overcome by two appr
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246 Hust et al.Fig. 1. Schematic de
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248 Hust et al.interaction during p
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250 Hust et al.3.4. Titering1. Inoc
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252 Hust et al.10. Shortly before u
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254 Hust et al.activity by preservi
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15A Bacterial/Yeast Merged Two-Hybr
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Screening in Yeast With a Bacterial
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16A Bacterial/Yeast Merged Two-Hybr
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Dual Bait-Compatible Bacterial Two-
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318 Thibodeau-Beganny and Joungbeen
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320 Thibodeau-Beganny and JoungFig.
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324 Thibodeau-Beganny and JoungTypi
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328 Thibodeau-Beganny and JoungPCR
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330 Thibodeau-Beganny and Joung16-1
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332 Thibodeau-Beganny and Joung2. P
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334 Thibodeau-Beganny and Joung11.
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336 IndexKknockin (gene knockin) 19
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