Bioinformatics for DNA Sequence Analysis.pdf - Index of

More documents

Recommendations

Info

M ETHODS IN M OLECULAR B IOLOGY TMBioinformatics for DNA SequenceAnalysisEdited byDavid PosadaDepartamento de Genética, Bioquímica e Inmunología,Facultad de Biología, Universidad de Vigo,Vigo, Spain
Page 8: To Mónica and Lucas
Page 14: ContentsPreface ...................
Page 18: ContributorsFEDERICO ABASCAL • De
Page 22: ContributorsxiiiJESSE ZANEVELD •
Page 26: 2 Menlove, Clement, and CrandallBy
Page 30: 4 Menlove, Clement, and CrandallTab
Page 34: 6 Menlove, Clement, and CrandallFig
Page 38: 8 Menlove, Clement, and CrandallTab
Page 42: 10 Menlove, Clement, and CrandallFi
Page 46: 12 Menlove, Clement, and CrandalllH
Page 52:
Similarity Searching Using BLAST 15
Page 56:
Page 60:
Page 64:
Page 70:
24 Egan et al.challenges faced by t
Page 74:
26 Egan et al.trees (termed guide t
Page 84:
Gene Orthology Assessment with Orth
Page 88:
Page 92:
Page 96:
Page 100:
Chapter 3Multiple Alignment of DNA
Page 104:
Multiple Alignment of DNA Sequences
Page 108:
Page 112:
Page 116:
Page 120:
Page 124:
Page 128:
Page 132:
Page 136:
Page 140:
Page 144:
Page 148:
Page 152:
Chapter 4SeqVis: A Tool for Detecti
Page 156:
SeqVis: Tool for Detecting Composit
Page 160:
Page 164:
Page 168:
Page 172:
Page 176:
Page 180:
Page 186:
82 Jermiin et al.points, and (ii) t
Page 190:
84 Jermiin et al.ATBTGGCACACTDTGGCA
Page 194:
86 Jermiin et al.3. Because the Cap
Page 198:
88 Jermiin et al.construction. Syst
Page 202:
90 Jermiin et al.69. Preparata, G.,
Page 206:
Chapter 5Selection of Models of DNA
Page 210:
Selection of Models of DNA Evolutio
Page 214:
Page 218:
Page 222:
Page 226:
Page 230:
Page 234:
Page 238:
Page 242:
Page 246:
Chapter 6Estimating Maximum Likelih
Page 250:
Estimating Maximum Likelihood Phylo
Page 254:
Page 258:
Page 262:
Page 266:
Page 270:
Page 274:
Page 278:
Page 282:
Page 286:
Page 290:
Page 294:
Page 298:
140 Creevey and McInerneyFig. 7.1.
Page 302:
142 Creevey and McInerneyapproach i
Page 306:
144 Creevey and McInerneygenomes se
Page 310:
146 Creevey and McInerneymore detai
Page 314:
148 Creevey and McInerney2. Program
Page 318:
Page 322:
Page 326:
Page 330:
Page 334:
158 Creevey and McInerneyThe second
Page 338:
160 Creevey and McInerneygenomes: t
Page 342:
Chapter 8Detecting Signatures of Se
Page 346:
Detecting Signatures of Selection f
Page 350:
Page 354:
Page 358:
Page 362:
Page 366:
Page 370:
Page 374:
Page 378:
Page 382:
Page 386:
186 MartinAt its very core the dete
Page 390:
188 MartinFig. 9.2. The General set
Page 394:
190 MartinBOOTSCAN windows should b
Page 398:
192 Martinreason is that RDP3 ident
Page 402:
194 Martinthe other indicating a cl
Page 406:
196 Martinunique recombination even
Page 410:
198 Martin3. Examples3.1. Producing
Page 414:
200 Martinpointer over the left mos
Page 418:
202 MartinFig. 9.5. Comparing recom
Page 422:
204 Martinphylogenetic trees that t
Page 426:
Chapter 10CodonExplorer: An Interac
Page 430:
CodonExplorer 209selection and muta
Page 434:
CodonExplorer 211Example: Searching
Page 438:
CodonExplorer 2132.2. Output Option
Page 442:
CodonExplorer 215Fig. 10.7. Selecti
Page 446:
CodonExplorer 217in each gene into
Page 450:
CodonExplorer 219Fig. 10.8. The cod
Page 454:
CodonExplorer 221between a subset o
Page 458:
CodonExplorer 223pull-down menu. Se
Page 462:
CodonExplorer 225Fig. 10.13. Finger
Page 466:
CodonExplorer 227checkbox, the desi
Page 470:
CodonExplorer 2294. For details on
Page 474:
CodonExplorer 2314. Efstratiadis, A
Page 478:
Chapter 11Genetic Code Prediction f
Page 482:
Genetic Code Prediction for Metazoa
Page 486:
Page 490:
Page 494:
Page 498:
Chapter 12Computational Gene Annota
Page 502:
Computational Gene Annotation 245De
Page 506:
Computational Gene Annotation 2473.
Page 510:
Computational Gene Annotation 249in
Page 514:
Computational Gene Annotation 2513.
Page 518:
Computational Gene Annotation 253Fi
Page 522:
Page 526:
Page 530:
Computational Gene Annotation 25910
Page 534:
Computational Gene Annotation 26129
Page 538:
264 Mariño-Ramírez et al.lower eu
Page 542:
266 Mariño-Ramírez et al.The anne
Page 546:
268 Mariño-Ramírez et al.Fig. 13.
Page 550:
270 Mariño-Ramírez et al.$aglam
Page 554:
272 Mariño-Ramírez et al.individu
Page 558:
274 Mariño-Ramírez et al.Fig. 13.
Page 562:
276 Mariño-Ramírez et al.Yamamoto
Page 566:
278 PevsnerThere are currently thre
Page 570:
280 PevsnerFig. 14.1. A portion of
Page 574:
282 Pevsnerand sequencing tracks (a
Page 578:
284 Pevsnerqueries). For DNA querie
Page 582:
286 PevsnerFor the top entry having
Page 586:
288 PevsnerFig. 14.6. The Table Bro
Page 590:
290 PevsnerComparative Genomics; tr
Page 594:
292 Pevsner5 0 -TCCTTGCCACGGGCCACCA
Page 598:
294 Pevsnercan differ dramatically
Page 602:
296 Pevsner(a)(b)(c)Fig. 14.10. Cre
Page 606:
298 PevsnerView the custom tracks.
Page 610:
300 PevsnerTrevanion, S., Ureta-Vid
Page 614:
Chapter 15Mining for SNPs and SSRs
Page 618:
Mining for SNPs and SSRs 305routine
Page 622:
Mining for SNPs and SSRs 307remains
Page 626:
Mining for SNPs and SSRs 3092.1. SN
Page 630:
Mining for SNPs and SSRs 311GC cont
Page 634:
Mining for SNPs and SSRs 313Fig. 15
Page 638:
Mining for SNPs and SSRs 315Table 1
Page 642:
Mining for SNPs and SSRs 317Fig. 15
Page 646:
Mining for SNPs and SSRs 319all pol
Page 650:
Mining for SNPs and SSRs 32127. Kat
Page 654:
324 Huda and JordanTE-related seque
Page 658:
326 Huda and Jordansequences (i.e.,
Page 662:
328 Huda and Jordan2.1.5. Method CE
Page 666:
330 Huda and JordanFig. 16.1. CENSO
Page 670:
332 Huda and JordanFig. 16.4. CENSO
Page 674:
334 Huda and JordanFig. 16.7. Repea
Page 678:
336 Huda and JordanReferences1. Lan
Page 682:
338 RozasDNA polymorphism informati
Page 686:
340 Rozasplotted. In this section,
Page 690:
342 RozasThe raggedness r statistic
Page 694:
344 Rozasdistribution of D. This di
Page 698:
346 Rozasempirical distribution of
Page 702:
348 Rozas3. Nucleotide diversity ca
Page 706:
350 Rozas12. Swofford, D. L. (1998)
Page 710:
352BIOINFORMATICS FOR DNA SEQUENCE
Page 714:
354BIOINFORMATICS FOR DNA SEQUENCE
show all

Bioinformatics for DNA Sequence Analysis.pdf - Index of

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?