Computational tools and Interoperability in Comparative ... - CBS

More documents

Recommendations

Info

Code Meaning Example C Coding CCCCCCCCCCCCC > Annotation start on forward strand .....>CCCC... < Annotation start on reverse strand ...CCCCTTT..... t 5S rRNA ..tttssss...... l 23S rRNA ...lllllcodesearch −cod U00096 . cod . gz −seq U00096 . fsa −pat ’(.{5 ,5} > s {1 ,1}) ’ 2 223773..223779 AAATTGA 3 3939833..3939839 AAATTGA 4 4033556..4033562 AAATTGA 5 4164684..4164690 AAATTGA 6 4206172..4206178 AAATTGA 7 3426782..3426776 ATTGAAG 8 2729177..2729171 ATTGAAG 9 >codesearch −cod U00096 . cod . gz −dat U00096 . sidd35 . gz : 1 , 4 −pat ’(.{5 ,5} > s {1 ,1}) ’\ 10 −format ’%0.2f ’ | tab2tbl −−window = ’ −5 ,2 ’ −org ’ E . coli K12 ’ −col blue 11 def org col −5 −4 −3 −2 −1 1 2 12 223773..223779 E . coli K12 blue 7.93 7.93 7.94 8.00 8.26 8.28 8.37 13 3939833..3939839 E . coli K12 blue 7.91 7.90 7.92 7.99 8.25 8.28 8.36 14 4033556..4033562 E . coli K12 blue 7.83 7.83 7.85 7.92 8.19 8.22 8.32 15 4164684..4164690 E . coli K12 blue 7.85 7.85 7.87 7.95 8.21 8.25 8.34 16 4206172..4206178 E . coli K12 blue 7.91 7.91 7.92 7.99 8.26 8.28 8.37 17 3426782..3426776 E . coli K12 blue 7.91 7.93 7.99 8.26 8.28 8.37 8.73 18 2729177..2729171 E . coli K12 blue 7.91 7.93 7.99 8.26 8.28 8.37 8.72 Using heatmap to generate energy landscape The R function heatmap described in chapter 2, was used to compare both SIDD profiles and the profiles of P1/P2 model scores. All promotor sequences were aligned first according to the peak score of the P1 model (near the expected site of P1) and second according to the peak score of the P2 model (near the expected site of P2). In figure 3.9 the model scores are visualized using the heatmap function on the green, heatmaps on the left, whereas the rightmost heatmaps contain the SIDD energies (blue) of the aligned promotor sequences. This analysis show that a deep drop in the SIDD energy occurs for approximately half of the promotor sequences, near the P1 site. 115
DNA melting and SIDD energy P1 -10 box 16S rRNA +1 P2 -10 box 16S rRNA +1 −500 −490 −480 −470 −460 −450 −440 −430 −420 −410 −400 −390 −380 −370 −360 −350 −340 −330 −320 −310 −300 −290 −280 −270 −260 −250 −240 −230 −220 −210 −200 −190 −180 −170 −160 −150 −140 −130 −120 −110 −100 −90 −80 −70 −60 −50 −40 −30 −20 −10 +1 +10 +20 +30 +40 +50 −500 −490 −480 −470 −460 −450 −440 −430 −420 −410 −400 −390 −380 −370 −360 −350 −340 −330 −320 −310 −300 −290 −280 −270 −260 −250 −240 −230 −220 −210 −200 −190 −180 −170 −160 −150 −140 −130 −120 −110 −100 −90 −80 −70 −60 −50 −40 −30 −20 −10 +1 +10 +20 +30 +40 +50 -22 34 Promotor sequences Model score (bits) 500 490 480 470 460 450 440 430 420 410 400 390 380 370 360 350 340 330 320 310 300 290 280 270 260 250 240 230 220 210 200 190 180 170 160 150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 +1 +10 +20 +30 +40 +50 +60 500 490 480 470 460 450 440 430 420 410 400 390 380 370 360 350 340 330 320 310 300 290 280 270 260 250 240 230 220 210 200 190 180 170 160 150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 +1 +10 +20 +30 +40 +50 SIDD energy (kcal/mol 5.8 10.0 Gaps are appended to each promotor region to adjust to maxima of the P1/P2 model scores Figure 3.9: E. coli and Shigella rrnB energy landscape visualized using the heatmap function. Each vertical column corresponds to a promotor sequence, whereas the horizontal rows represent average values over 10 bp within each sequence. Coordinates labeled on the horizontal rows are relative to the 16S rRNA gene start. The upper heatmaps show P1 whereas the lower heatmaps show P2. Leftmost heatmaps show P1/P2 model scores in green, whereas rightmost heatmaps show the SIDD energy in blue. 116
Page 1 and 2:
Peter Fischer Hallin | 2009 Peter F
Page 4:
Preface This Ph.D. thesis is writte
Page 7 and 8:
thesis, the work is just being publ
Page 9 and 10:
ved at blive publiceret i Standards
Page 11 and 12:
viii
Page 13 and 14:
Paper VI [Lagesen K, Hallin P] 1 ,
Page 15 and 16:
xii
Page 17 and 18:
3.3.3 Refining E. coli and Shigella
Page 19 and 20:
xvi
Page 21 and 22:
xviii 2.17 Pan- and core-genome plo
Page 24 and 25:
Chapter 1 Introduction Introduction
Page 26 and 27:
Chapter 2 Comparative Genomics 2.1
Page 28 and 29:
Comparative Genomics the publicly a
Page 30 and 31:
Comparative Genomics source CDS tot
Page 32 and 33:
Comparative Genomics 1 mysql -N -B
Page 34 and 35:
Listing 2.8: R code to generate a 2
Page 36 and 37:
1st U C A G U 2nd position C A G 3r
Page 38 and 39:
1st U C A G U 2nd position C A G 3r
Page 40 and 41:
Escherichia coli strain K-12, subst
Page 42 and 43:
Comparative Genomics
Page 44 and 45:
3M 2.5M 3.5M 2.5M 2M 0M 2M 0.5M B.
Page 46 and 47:
Streptococcus Escherichia Bacillus
Page 48 and 49:
2.4 Summary Comparative Genomics Th
Page 50 and 51:
Comparative Genomics 2.5 Instant in
Page 52 and 53:
‘ReSourCe is he best online submi
Page 54 and 55:
up to a total of 41 different E. co
Page 56 and 57:
Fig. 2 Genes (or segments) from eac
Page 58 and 59:
Fig. 5 BLASTatlas of Clostridium bo
Page 60 and 61:
different applications, such as ide
Page 62 and 63:
1 Comparative Genomics 2.7 Paper II
Page 64 and 65:
166 literally millions of bacterial
Page 66 and 67:
168
Page 68 and 69:
170 resistance genes on mobile gene
Page 70 and 71:
172 involved in generating diversit
Page 72 and 73:
174 recipient DNA. A feature observ
Page 74 and 75:
176 Fig. 5 Genome length distributi
Page 76 and 77:
178
Page 78 and 79:
180 reasons why organisms remain un
Page 80 and 81:
182 A final problem has to do with
Page 82 and 83:
184 Middendorf B, Hochhut B, Leipol
Page 84 and 85:
1 Comparative Genomics 2.8 Paper II
Page 86 and 87:
2 O. N. Reva et al. Fig. 1. Genome
Page 88 and 89: 4 O. N. Reva et al. decrease of the
Page 90 and 91: 6 O. N. Reva et al. of which are kn
Page 92 and 93: 8 O. N. Reva et al. compiled into a
Page 94 and 95: 10 O. N. Reva et al. encoded by a c
Page 96 and 97: 12 O. N. Reva et al. systems and ef
Page 98 and 99: 1 2.9 Paper IV: The origins of Vibr
Page 100 and 101: phylogenies based on alternative ho
Page 102 and 103: Figure 1 Phylogenetic tree of the 1
Page 104 and 105: 25000 20000 15000 10000 5000 0 Pan
Page 106 and 107: Gap F 2M 2.5M Gap E 875k 750k 625k
Page 108 and 109: Table 2 A selection of genes locate
Page 110 and 111: Open Access This article is distrib
Page 112 and 113: 1 Comparative Genomics 2.10 Paper V
Page 114 and 115: 4314 74 Tools Abstract: Of the plet
Page 116 and 117: 4316 74 Tools Size distribution of
Page 118 and 119: 4318 74 Tools Genome atlas Intrinsi
Page 120 and 121: 4320 74 Tools Genome atlas Intrinsi
Page 122 and 123: 4322 74 Tools for Comparison of Bac
Page 124 and 125: 4324 74 Tools for Comparison of Bac
Page 126 and 127: 4326 74 Tools information, as genet
Page 128 and 129: Chapter 3 rRNA operons and promoter
Page 130 and 131: tuB murI Fis III Fis II Fis I UP -3
Page 132 and 133: Bits 2.0 1.5 1.0 0.5 0.0 Bits 2.0 1
Page 134 and 135: RNA operons and promoter analysis O
Page 136 and 137: Bits 2.0 1.5 1.0 0.5 0.0 Bits T A T
Page 140 and 141: RNA operons and promoter analysis 3
Page 142 and 143: P2 -10 -35 UP P1 -10 -35 UP FIS FIS
Page 144 and 145: 1 rRNA operons and promoter analysi
Page 146 and 147: Using HMMs also simplifies the use
Page 148 and 149: Information content Information con
Page 150 and 151: of the annotation. Some of the majo
Page 152 and 153: where match states stop around 10 c
Page 154 and 155: 1 rRNA operons and promoter analysi
Page 156 and 157: synthesis in flow cells to simultan
Page 158 and 159: Read absence. A boolean where ‘on
Page 160 and 161: Hallin, et al. Figure 4 | The dataf
Page 162 and 163: Genome homology: Comparing multiple
Page 164 and 165: ing platform-‐independent Java
Page 166 and 167: 34. Wang H, Noordewier M, Benham CJ
Page 168 and 169: Chapter 4 Web Services and Interope
Page 170 and 171: Web Services and Interoperability i
Page 178 and 179: Chapter 5 Conclusion and perspectiv
Page 180 and 181: Appendix A Appendix: Workshops, tea
Page 182 and 183: Appendix B Appendix: Ph.D. study pl
Page 184 and 185: Danmarks Tekniske Universitet AFI,
Page 186 and 187: Danmarks Tekniske Universitet AFI,
Page 188 and 189:
Appendix C Appendix: Courses C.1 Gl
Page 190 and 191:
D.2 Sample output from queryGenomes
Page 192 and 193:
Appendix: Software 13 w a r n " $ o
Page 194 and 195:
Appendix: Software 109 m y ( $ m i
Page 196 and 197:
Appendix: Software 25 [ ] A l t e r
Page 198 and 199:
BIBLIOGRAPHY J. Rogers, P. F. Stadl
Page 200 and 201:
BIBLIOGRAPHY Q. Jin, Z. Yuan, J. Xu
Page 202 and 203:
BIBLIOGRAPHY Velicer, F.-J. Vorholt
show all

Computational tools and Interoperability in Comparative ... - CBS

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

Delete template?

Save as template?