Protein networks as a scaffold for structuring other data
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This document discusses using protein interaction networks as a scaffold to integrate other biological data sources. It describes several high-throughput studies that mapped protein interaction networks in yeast, worm, fruit fly and human. While the protein interaction networks are incomplete and have high false positive rates, topology-based scoring and other filtering methods can be used to identify high-confidence interactions. The document goes on to discuss integrating protein interaction networks with gene expression time series data from yeast to build temporal networks and identify periodically expressed genes and modules involved in cell cycle regulation.
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Protein networks as a scaffold for structuring other data
- 1. Protein networks as a scaffold for structuring other data Lars Juhl Jensen EMBL Heidelberg
- 4. Chapter 1
- 6. what is an interaction?
- 12. high-throughput
- 13. S. cerevisiae
- 14. Uetz et al.
- 15. Ito et al.
- 16. Gavin et al.
- 17. Ho et al.
- 18. Gavin et al.
- 19. Krogan et al.
- 20. C. elegans
- 21. Li et al.
- 22. D. melanogaster
- 23. Giot et al.
- 24. H. sapiens
- 25. Stelzl et al.
- 26. Rual et al.
- 28. yeehaa!
- 29. network topology
- 32. scale-free
- 34. hubs
- 35. essentiality
- 37. targeted attacks
- 38. artefacts
- 41. Han et al.
- 43. can we trust this data?
- 45. (incomplete)
- 46. yeast two-hybrid
- 47. 1936 13 4 4 1385 65 18465 Stelzl et al. Rual et al. Small-scale studies
- 48. 32 0 3 4 18 4 23 Stelzl et al. Rual et al. Small-scale studies
- 49. 62 8 39 Small-scale studies Stelzl et al. Rual et al. 852 17 473 432 69 260
- 50. 3.5% and 21% sensitivity
- 52. five years ago
- 53. yeast two-hybrid
- 54. 1150 117 117 72 4053 118 4469 Uetz et al. Ito et al. Small-scale studies
- 55. 162 53 34 72 180 29 338 Uetz et al. Ito et al. Small-scale studies
- 56. 511 189 616 Small-scale studies Uetz et al. Ito et al. 439 178 759 897 190 1347
- 57. 19% and 12% sensitivity
- 58. three years ago
- 60. 14186 784 1178 287 19492 230 3475 Gavin et al. Ho et al. Small-scale studies
- 61. 2341 125 656 287 2725 42 149 Gavin et al. Ho et al. Small-scale studies
- 62. 4431 1465 5041 Small-scale studies Gavin et al. Ho et al. 14913 1071 632 8047 517 746
- 63. 63% and 41% sensitivity
- 68. what can we do about it?
- 71. log[(N 12 · N)/((N 1 +1) · (N 2 +1))]
- 72. yeast two-hybrid
- 73. -log((N 1 +1) · (N 2 +1))
- 78. filtering
- 79. high-throughput
- 81. high-confidence
- 82. Chapter 2
- 83. expression data
- 84. S. cerevisiae
- 91. S. cerevisiae
- 92. Cho et al.
- 93. Spellman et al.
- 94. yeehaa!
- 95. Zhao et al.
- 96. Langmead et al.
- 97. Johansson et al.
- 98. Wichert et al.
- 99. Luan and Li
- 100. Lu et al.
- 101. Ahdesm äki et al.
- 102. Willbrand et al.
- 103. Chen et al.
- 104. Qiu et al.
- 105. Ahnert et al.
- 106. Andersson et al.
- 107. no benchmarking
- 108. reanalysis
- 109. benchmarking
- 111. no progress
- 112. no benchmarking
- 114. Chapter 3
- 115. 1+2 = 3
- 116. expression data
- 118. protein interactions
- 120. temporal network
- 122. benchmarking
- 125. very low error rate
- 126. discovery tool
- 130. novel module
- 132. global statements
- 133. dynamic and static
- 136. CDK–cyclin complexes
- 138. consistent timing
- 145. how can we test this?
- 147. Chapter 4
- 148. more expression data
- 149. S. cerevisiae
- 154. S. pombe
- 155. Rustici et al.
- 156. (good job)
- 157. Peng et al.
- 158. Oliva et al.
- 159. no benchmarking
- 160. no integration
- 161. reanalysis
- 162. benchmarking
- 164. no progress
- 165. no benchmarking
- 166. no integration
- 168. H. sapiens
- 169. Whitfield et al.
- 170. reanalysis
- 171. benchmarking
- 173. A. thaliana
- 174. Menges et al.
- 175. reanalysis
- 176. benchmarking
- 178. list of genes
- 179. peak times
- 180. Chapter 5
- 182. orthology assignment
- 183. peak times
- 184. not comparable
- 185. time warping
- 188. not conserved
- 189. individual genes
- 191. protein complexes
- 192. DNA polymerases
- 196. chromatid cohesion
- 198. reproduces what is known
- 199. known differences
- 200. timing has changed
- 201. identity has changed
- 202. self-consistent
- 203. make sense
- 204. protein complexes
- 205. individual genes
- 206. broader perspective
- 207. protein networks
- 208. context
- 209. understanding
- 210. Acknowledgments Ulrik de Lichtenberg Thomas Skøt Jensen Christian von Mering Søren Brunak Peer Bork