Systems biology - Understanding biology at the systems level

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Systems biology - Understanding biology at the systems level

  1. 1. Systems biologyUnderstanding biology at the systems level Lars Juhl Jensen
  2. 2. traditional biology
  3. 3. can a biologist fix a radio?
  4. 4. Lazebnik, Biochemistry, 2004
  5. 5. one gene
  6. 6. one postdoc
  7. 7. all aspects
  8. 8. knockout phenotype
  9. 9. Lazebnik, Biochemistry, 2004
  10. 10. one gene
  11. 11. high-throughput biology
  12. 12. one technology
  13. 13. one lab
  14. 14. all genes
  15. 15. one aspect
  16. 16. systems biology
  17. 17. complete systems
  18. 18. all aspects
  19. 19. all genes
  20. 20. systems-level properties
  21. 21. two subfields
  22. 22. mathematical modeling
  23. 23. small systems
  24. 24. data integration
  25. 25. large systems
  26. 26. the system
  27. 27. mitotic cell cycle
  28. 28. grow and divide
  29. 29. one cell
  30. 30. two cells
  31. 31. four phases
  32. 32. G1 phase
  33. 33. growth
  34. 34. S phase
  35. 35. DNA replication
  36. 36. G2 phase
  37. 37. growth
  38. 38. M phase
  39. 39. cell division
  40. 40. regulation
  41. 41. gene expression
  42. 42. phosphorylation
  43. 43. targeted degradation
  44. 44. protein interactions
  45. 45. cell cycle modeling
  46. 46. core cell cycle
  47. 47. Chen, Mol. Biol. Cell, 2004
  48. 48. many equations
  49. 49. Chen, Mol. Biol. Cell, 2004
  50. 50. simulation
  51. 51. Chen, Mol. Biol. Cell, 2004
  52. 52. many parameters
  53. 53. Chen, Mol. Biol. Cell, 2004
  54. 54. requires detailed knowledge
  55. 55. cell cycle analysis
  56. 56. gene expression
  57. 57. cell cultures
  58. 58. synchronization
  59. 59. microarrays
  60. 60. time courses
  61. 61. Gauthier et al., Nucleic Acids Research, 2007
  62. 62. cycling genes
  63. 63. time of peak expression
  64. 64. exercise 1
  65. 65. http://cyclebase.org
  66. 66. S. cerevisiae
  67. 67. RNR1, RNR2, RNR3, RNR4
  68. 68. S. pombe
  69. 69. cdc22, suc22
  70. 70. which genes cycle?
  71. 71. do time courses agree?
  72. 72. do orthologs agree?
  73. 73. do paralogs agree?
  74. 74. protein networks
  75. 75. guilt by association
  76. 76. STRING
  77. 77. >1100 genomes
  78. 78. genomic context
  79. 79. gene fusion
  80. 80. Korbel et al., Nature Biotechnology, 2004
  81. 81. conserved neighborhood
  82. 82. Korbel et al., Nature Biotechnology, 2004
  83. 83. phylogenetic profiles
  84. 84. Korbel et al., Nature Biotechnology, 2004
  85. 85. protein interactions
  86. 86. Jensen & Bork, Science, 2008
  87. 87. genetic interactions
  88. 88. Beyer et al., Nature Reviews Genetics, 2007
  89. 89. gene coexpression
  90. 90. curated knowledge
  91. 91. Letunic & Bork, Trends in Biochemical Sciences, 2008
  92. 92. >10 km
  93. 93. text mining
  94. 94. Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009
  95. 95. co-mentioning
  96. 96. NLPNatural Language Processing
  97. 97. different sources
  98. 98. Ensembl
  99. 99. RefSeq
  100. 100. BINDBiomolecular Interaction Network Database
  101. 101. BioGRIDGeneral Repository for Interaction Datasets
  102. 102. DIPDatabase of Interacting Proteins
  103. 103. IntAct
  104. 104. MINTMolecular Interactions Database
  105. 105. HPRDHuman Protein Reference Database
  106. 106. PDBProtein Data Bank
  107. 107. GEOGene Expression Omnibus
  108. 108. MIPSMunich Information center for Protein Sequences
  109. 109. Gene Ontology
  110. 110. BioCyc
  111. 111. KEGGKyoto Encyclopedia of Genes and Genomes
  112. 112. PIDNCI-Nature Pathway Interaction Database
  113. 113. Reactome
  114. 114. different formats
  115. 115. different names
  116. 116. CDC2
  117. 117. CDK1
  118. 118. P06493
  119. 119. not comparable
  120. 120. variable quality
  121. 121. confidence scores
  122. 122. calibrate to gold standard
  123. 123. von Mering et al., Nucleic Acids Research, 2005
  124. 124. transfer by orthology
  125. 125. von Mering et al., Nucleic Acids Research, 2005
  126. 126. combine scores
  127. 127. exercise 2
  128. 128. http://string-db.org
  129. 129. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  130. 130. changing parameters
  131. 131. high confidence only
  132. 132. experiments only
  133. 133. evidence viewers
  134. 134. which interact functionally?
  135. 135. which interact physically?
  136. 136. complex regulation
  137. 137. time of peak expression
  138. 138. protein interactions
  139. 139. temporal network
  140. 140. de Lichtenberg, Jensen et al., Science, 2005
  141. 141. dynamic vs. static subunits
  142. 142. de Lichtenberg, Jensen et al., Science, 2005
  143. 143. just-in-time assembly
  144. 144. de Lichtenberg, Jensen et al., Cell Cycle, 2007
  145. 145. evolutionary flexibility
  146. 146. orthologs and paralogs
  147. 147. Jensen, Jensen, de Lichtenberg et al., Nature, 2006
  148. 148. protein complexes
  149. 149. Jensen, Jensen, de Lichtenberg et al., Nature, 2006
  150. 150. exercise 3
  151. 151. http://cyclebase-string.jensenlab.org
  152. 152. network expansion
  153. 153. what does SML1 do?
  154. 154. when is SML1 expressed?
  155. 155. how does that make sense?
  156. 156. multi-layer regulation
  157. 157. phosphorylation
  158. 158. CDK substrates
  159. 159. low-throughput data
  160. 160. high-throughput data
  161. 161. NetPhosK
  162. 162. correlation
  163. 163. Jensen, Jensen, de Lichtenberg et al., Nature, 2006
  164. 164. Jensen, Jensen, de Lichtenberg et al., Nature, 2006
  165. 165. bias
  166. 166. correlated changes
  167. 167. removes the bias
  168. 168. Jensen, Jensen, de Lichtenberg et al., Nature, 2006
  169. 169. co-evolution
  170. 170. disease networks
  171. 171. human proteins
  172. 172. >8,000 disease terms
  173. 173. text mining
  174. 174. co-mentioning
  175. 175. exercise 4
  176. 176. http://diseases.jensenlab.org
  177. 177. TYMS disease associations
  178. 178. inspect the evidence
  179. 179. colorectal cancer network
  180. 180. chemical networks
  181. 181. STITCH
  182. 182. STRING + chemicals
  183. 183. PubChem compounds
  184. 184. >74,000 small molecules
  185. 185. experimental data
  186. 186. BindingDB
  187. 187. ChEMBL
  188. 188. PDSP KiPsycoactive Drug Screening Program
  189. 189. PDBProtein Data Bank
  190. 190. drug targets
  191. 191. CTDComparative Toxicogenomics Database
  192. 192. DrugBank
  193. 193. GLIDAGPCR-Ligand Database
  194. 194. Matador
  195. 195. TTDTherapeutic Target Database
  196. 196. metabolic pathways
  197. 197. BioCyc
  198. 198. KEGGKyoto Encyclopedia of Genes and Genomes
  199. 199. Reactome
  200. 200. text mining
  201. 201. co-mentioning
  202. 202. NLPNatural Language Processing
  203. 203. same issues as for proteins
  204. 204. only worse
  205. 205. exercise 5
  206. 206. http://stitch-db.org
  207. 207. chemical network for TYMS
  208. 208. Kuhn et al., Nucleic Acids Research, 2012
  209. 209. network expansion
  210. 210. which role has thymidylate?
  211. 211. which role has dUMP?
  212. 212. which role has Pemetrexed?

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