Networks of proteins and diseases

567
-1

Published on

Published in: Technology
0 Comments
3 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
567
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
19
Comments
0
Likes
3
Embeds 0
No embeds

No notes for slide

Networks of proteins and diseases

  1. 1. Networks of proteins and diseases Lars Juhl Jensen
  2. 2. three parts
  3. 3. protein networks
  4. 4. localization & disease
  5. 5. disease networks
  6. 6. protein networks
  7. 7. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  8. 8. computational predictions
  9. 9. gene fusion
  10. 10. Korbel et al., Nature Biotechnology, 2004
  11. 11. experimental data
  12. 12. physical interactions
  13. 13. Jensen & Bork, Science, 2008
  14. 14. curated knowledge
  15. 15. metabolic pathways
  16. 16. Letunic & Bork, Trends in Biochemical Sciences, 2008
  17. 17. text mining
  18. 18. dictionary-based approach
  19. 19. co-mentioning
  20. 20. many databases
  21. 21. different formats
  22. 22. different identifiers
  23. 23. variable quality
  24. 24. not comparable
  25. 25. hard work
  26. 26. quality scores
  27. 27. von Mering et al., Nucleic Acids Research, 2005
  28. 28. calibrate vs. gold standard
  29. 29. von Mering et al., Nucleic Acids Research, 2005
  30. 30. localization & disease
  31. 31. general approach
  32. 32. suite of web resources
  33. 33. curated knowledge
  34. 34. experimental data
  35. 35. text mining
  36. 36. computational predictions
  37. 37. quality scores
  38. 38. data visualization
  39. 39. compartments
  40. 40. Gene Ontology
  41. 41. compartments.jensenlab.org
  42. 42. tissues
  43. 43. BRENDA Tissue Ontology
  44. 44. tissues.jensenlab.org
  45. 45. diseases
  46. 46. Disease Ontology
  47. 47. removal of gene symbols
  48. 48. addition of links
  49. 49. evidence viewers
  50. 50. web services
  51. 51. diseases.jensenlab.org
  52. 52. download files
  53. 53. disease networks
  54. 54. electronic health records
  55. 55. Jensen et al., Nature Reviews Genetics, 2012
  56. 56. structured data
  57. 57. Jensen et al., Nature Reviews Genetics, 2012
  58. 58. unstructured data
  59. 59. comorbidity
  60. 60. Jensen et al., Nature Reviews Genetics, 2012
  61. 61. Roque et al., PLoS Computational Biology, 2011
  62. 62. in Danish
  63. 63. multiple testing
  64. 64. confounding factors
  65. 65. age and gender
  66. 66. reporting bias
  67. 67. molecular basis
  68. 68. protein–disease links
  69. 69. protein networks
  70. 70. Acknowledgments STRING Christian von Mering Damian Szklarczyk Michael Kuhn Manuel Stark Samuel Chaffron Chris Creevey Jean Muller Tobias Doerks Philippe Julien Alexander Roth Milan Simonovic Jan Korbel Berend Snel Martijn Huynen Peer Bork Text mining Sune Frankild Evangelos Pafilis Alberto Santos Kalliopi Tsafou Janos Binder Lucia Fanini Sarah Faulwetter Christina Pavloudi Julia Schnetzer Aikaterini Vasileiadou Heiko Horn Michael Kuhn Nigel Brown Reinhard Schneider Sean O’Donoghue EHR mining Robert Eriksson Peter Bjødstrup Jensen Anders Boeck Jensen Francisco S. Roque Henriette Schmock Marlene Dalgaard Massimo Andreatta Thomas Hansen Karen Søeby Søren Bredkjær Anders Juul Tudor Oprea Pope Moseley Thomas Werge Søren Brunak
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×