Guidelines for Genome-Scale Analysis of Biological Rhythms

  1. Hughes, Michael E.
  2. Abruzzi, Katherine C.
  3. Allada, Ravi
  4. Anafi, Ron
  5. Arpat, Alaaddin Bulak
  6. Asher, Gad
  7. Baldi, Pierre
  8. de Bekker, Charissa
  9. Bell-Pedersen, Deborah
  10. Blau, Justin
  11. Brown, Steve
  12. Ceriani, M. Fernanda
  13. Chen, Zheng
  14. Chiu, Joanna C.
  15. Cox, Juergen
  16. Crowell, Alexander M.
  17. DeBruyne, Jason P.
  18. Dijk, Derk-Jan
  19. DiTacchio, Luciano
  20. Doyle, Francis J.
  21. Duffield, Giles E.
  22. Dunlap, Jay C.
  23. Eckel-Mahan, Kristin
  24. Esser, Karyn A.
  25. FitzGerald, Garret A.
  26. Forger, Daniel B.
  27. Francey, Lauren J.
  28. Fu, Ying-Hui
  29. Gachon, Frédéric
  30. Gatfield, David
  31. de Goede, Paul
  32. Golden, Susan S.
  33. Green, Carla
  34. Harer, John
  35. Harmer, Stacey
  36. Haspel, Jeff
  37. Hastings, Michael H.
  38. Herzel, Hanspeter
  39. Herzog, Erik D.
  40. Hoffmann, Christy
  41. Hong, Christian
  42. Hughey, Jacob J.
  43. Hurley, Jennifer M.
  44. de la Iglesia, Horacio O.
  45. Johnson, Carl
  46. Kay, Steve A.
  47. Koike, Nobuya
  48. Kornacker, Karl
  49. Kramer, Achim
  50. Lamia, Katja
  51. Leise, Tanya
  52. Lewis, Scott A.
  53. Li, Jiajia
  54. Li, Xiaodong
  55. Liu, Andrew C.
  56. Loros, Jennifer J.
  57. Martino, Tami A.
  58. Menet, Jerome S.
  59. Merrow, Martha
  60. Millar, Andrew J.
  61. Mockler, Todd
  62. Naef, Felix
  63. Nagoshi, Emi
  64. Nitabach, Michael N.
  65. Olmedo, Maria
  66. Nusinow, Dmitri A.
  67. Ptáček, Louis J.
  68. Rand, David
  69. Reddy, Akhilesh B.
  70. Robles, Maria S.
  71. Roenneberg, Till
  72. Rosbash, Michael
  73. Ruben, Marc D.
  74. Rund, Samuel S.C.
  75. Sancar, Aziz
  76. Sassone-Corsi, Paolo
  77. Sehgal, Amita
  78. Sherrill-Mix, Scott
  79. Skene, Debra J.
  80. Storch, Kai-Florian
  81. Takahashi, Joseph S.
  82. Ueda, Hiroki R.
  83. Wang, Han
  84. Weitz, Charles
  85. Westermark, Pål ORCID logo
  86. Wijnen, Herman
  87. Xu, Ying
  88. Wu, Gang
  89. Yoo, Seung-Hee
  90. Young, Michael
  91. Zhang, Eric Erquan
  92. Zielinski, Tomasz
  93. Hogenesch, John B.

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WeightNameValue
1000 Titel
  • Guidelines for Genome-Scale Analysis of Biological Rhythms
1000 Autor/in
  1. Hughes, Michael E. |
  2. Abruzzi, Katherine C. |
  3. Allada, Ravi |
  4. Anafi, Ron |
  5. Arpat, Alaaddin Bulak |
  6. Asher, Gad |
  7. Baldi, Pierre |
  8. de Bekker, Charissa |
  9. Bell-Pedersen, Deborah |
  10. Blau, Justin |
  11. Brown, Steve |
  12. Ceriani, M. Fernanda |
  13. Chen, Zheng |
  14. Chiu, Joanna C. |
  15. Cox, Juergen |
  16. Crowell, Alexander M. |
  17. DeBruyne, Jason P. |
  18. Dijk, Derk-Jan |
  19. DiTacchio, Luciano |
  20. Doyle, Francis J. |
  21. Duffield, Giles E. |
  22. Dunlap, Jay C. |
  23. Eckel-Mahan, Kristin |
  24. Esser, Karyn A. |
  25. FitzGerald, Garret A. |
  26. Forger, Daniel B. |
  27. Francey, Lauren J. |
  28. Fu, Ying-Hui |
  29. Gachon, Frédéric |
  30. Gatfield, David |
  31. de Goede, Paul |
  32. Golden, Susan S. |
  33. Green, Carla |
  34. Harer, John |
  35. Harmer, Stacey |
  36. Haspel, Jeff |
  37. Hastings, Michael H. |
  38. Herzel, Hanspeter |
  39. Herzog, Erik D. |
  40. Hoffmann, Christy |
  41. Hong, Christian |
  42. Hughey, Jacob J. |
  43. Hurley, Jennifer M. |
  44. de la Iglesia, Horacio O. |
  45. Johnson, Carl |
  46. Kay, Steve A. |
  47. Koike, Nobuya |
  48. Kornacker, Karl |
  49. Kramer, Achim |
  50. Lamia, Katja |
  51. Leise, Tanya |
  52. Lewis, Scott A. |
  53. Li, Jiajia |
  54. Li, Xiaodong |
  55. Liu, Andrew C. |
  56. Loros, Jennifer J. |
  57. Martino, Tami A. |
  58. Menet, Jerome S. |
  59. Merrow, Martha |
  60. Millar, Andrew J. |
  61. Mockler, Todd |
  62. Naef, Felix |
  63. Nagoshi, Emi |
  64. Nitabach, Michael N. |
  65. Olmedo, Maria |
  66. Nusinow, Dmitri A. |
  67. Ptáček, Louis J. |
  68. Rand, David |
  69. Reddy, Akhilesh B. |
  70. Robles, Maria S. |
  71. Roenneberg, Till |
  72. Rosbash, Michael |
  73. Ruben, Marc D. |
  74. Rund, Samuel S.C. |
  75. Sancar, Aziz |
  76. Sassone-Corsi, Paolo |
  77. Sehgal, Amita |
  78. Sherrill-Mix, Scott |
  79. Skene, Debra J. |
  80. Storch, Kai-Florian |
  81. Takahashi, Joseph S. |
  82. Ueda, Hiroki R. |
  83. Wang, Han |
  84. Weitz, Charles |
  85. Westermark, Pål |
  86. Wijnen, Herman |
  87. Xu, Ying |
  88. Wu, Gang |
  89. Yoo, Seung-Hee |
  90. Young, Michael |
  91. Zhang, Eric Erquan |
  92. Zielinski, Tomasz |
  93. Hogenesch, John B. |
1000 Erscheinungsjahr 2017
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2017-11-03
1000 Erschienen in
1000 Quellenangabe
  • 32(5): 380-393
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2017
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1177/0748730417728663 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5692188/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.
1000 Sacherschließung
lokal guidelines
lokal RNA-seq
lokal systems biology
lokal ChIP-seq
lokal biostatistics
lokal metabolomics
lokal functional genomics
lokal computational biology
lokal circadian rhythms
lokal proteomics
lokal diurnal rhythms
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. NIAMS |
  2. Department of Medicine at Washington University |
  3. DARPA |
  4. Department of Biology at the University of Central Florida |
  5. National Institutes of Health (NIH) |
  6. Robert A. Welch Foundation |
  7. National Institute on Aging |
  8. National Science Foundation (NSF) |
  9. National Institute of Neurological Disorders and Stroke (NINDS) |
  10. National Institute of General Medical Sciences (NIGMS) |
  11. Biotechnology and Biological Sciences Research Council |
  12. Royal Society |
  13. Eck Institute for Global Health |
  14. UK Medical Research Council |
  15. National Institute of Allergy and Infectious Diseases |
  16. National Institute of Biomedical Imaging and Bioengineering |
  17. Department of Biological Sciences at Rensselaer Polytechnic Institute |
  18. JSPS KAKENHI |
  19. Deutsche Forschungsgemeinschaft (DFG) |
  20. National Institute of Diabetes and Digestive and Kidney Diseases |
  21. Canadian Institutes of Health Research |
  22. Heart and Stroke Foundation of Canada |
  23. Dutch Foundation for Technology and Science (STW) |
  24. Volkswagen Foundation |
  25. Ludwig-Maximilians University Munich |
  26. Spanish Ministerio de Economía y Competitividad |
  27. Wellcome Trust |
  28. Cancer Research UK |
  29. U.K. Medical Research Council |
  30. National Basic Research Program of China |
  31. National Natural Science Foundation of China |
  32. Leibniz Institute for Farm Animal Biology |
  33. Biotechnology and Biological Science Research Council |
  34. European Union |
1000 Fördernummer
  1. 1R21AR069266
  2. -
  3. D17AP00002
  4. -
  5. GM063911; R01 GM102225; R35GM118021; U01EB022546; R35GM118290; R01GM112991; R01GM111387; R01AG045795; R01GM069418; U01EB021956; R01NS095367; R01GM104991; R01 NS094211; R35GM118022
  6. AU-1731
  7. R01AG045828
  8. IOS 1456297; IOS1238040; IOS-1456796
  9. U54 NS083932; R01NS054794; R01NS091070; 5R01NS05479
  10. SC1 GM109861; R01-GM087508; R01GM098931; R01GM114424
  11. -
  12. NF140517
  13. -
  14. MC_U105170643
  15. U19AI116491
  16. 1U01EB022546
  17. -
  18. JP26293048
  19. SFB740/D2; TRR186/A17
  20. DK097164
  21. -
  22. -
  23. -
  24. -
  25. -
  26. RYC-2014-15551
  27. 100333/Z/12/Z; FC001534
  28. FC001534
  29. FC001534
  30. 973; 2012CB947600
  31. 31030062; 81570171; 81070455
  32. -
  33. BB/L023067/1
  34. 618563
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
  5. -
  6. -
  7. -
  8. -
  9. -
  10. -
  11. -
  12. Royal Society Wolfson Research Merit Award
  13. -
  14. -
  15. -
  16. -
  17. -
  18. -
  19. -
  20. -
  21. -
  22. -
  23. -
  24. -
  25. -
  26. Ramón y Cajal
  27. -
  28. -
  29. -
  30. -
  31. -
  32. -
  33. -
  34. Marie Sklodowska Curie Career Integration
1000 Dateien
  1. Guidelines for Genome-Scale Analysis of Biological Rhythms
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer NIAMS |
    1000 Förderprogramm -
    1000 Fördernummer 1R21AR069266
  2. 1000 joinedFunding-child
    1000 Förderer Department of Medicine at Washington University |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer DARPA |
    1000 Förderprogramm -
    1000 Fördernummer D17AP00002
  4. 1000 joinedFunding-child
    1000 Förderer Department of Biology at the University of Central Florida |
    1000 Förderprogramm -
    1000 Fördernummer -
  5. 1000 joinedFunding-child
    1000 Förderer National Institutes of Health (NIH) |
    1000 Förderprogramm -
    1000 Fördernummer GM063911; R01 GM102225; R35GM118021; U01EB022546; R35GM118290; R01GM112991; R01GM111387; R01AG045795; R01GM069418; U01EB021956; R01NS095367; R01GM104991; R01 NS094211; R35GM118022
  6. 1000 joinedFunding-child
    1000 Förderer Robert A. Welch Foundation |
    1000 Förderprogramm -
    1000 Fördernummer AU-1731
  7. 1000 joinedFunding-child
    1000 Förderer National Institute on Aging |
    1000 Förderprogramm -
    1000 Fördernummer R01AG045828
  8. 1000 joinedFunding-child
    1000 Förderer National Science Foundation (NSF) |
    1000 Förderprogramm -
    1000 Fördernummer IOS 1456297; IOS1238040; IOS-1456796
  9. 1000 joinedFunding-child
    1000 Förderer National Institute of Neurological Disorders and Stroke (NINDS) |
    1000 Förderprogramm -
    1000 Fördernummer U54 NS083932; R01NS054794; R01NS091070; 5R01NS05479
  10. 1000 joinedFunding-child
    1000 Förderer National Institute of General Medical Sciences (NIGMS) |
    1000 Förderprogramm -
    1000 Fördernummer SC1 GM109861; R01-GM087508; R01GM098931; R01GM114424
  11. 1000 joinedFunding-child
    1000 Förderer Biotechnology and Biological Sciences Research Council |
    1000 Förderprogramm -
    1000 Fördernummer -
  12. 1000 joinedFunding-child
    1000 Förderer Royal Society |
    1000 Förderprogramm Royal Society Wolfson Research Merit Award
    1000 Fördernummer NF140517
  13. 1000 joinedFunding-child
    1000 Förderer Eck Institute for Global Health |
    1000 Förderprogramm -
    1000 Fördernummer -
  14. 1000 joinedFunding-child
    1000 Förderer UK Medical Research Council |
    1000 Förderprogramm -
    1000 Fördernummer MC_U105170643
  15. 1000 joinedFunding-child
    1000 Förderer National Institute of Allergy and Infectious Diseases |
    1000 Förderprogramm -
    1000 Fördernummer U19AI116491
  16. 1000 joinedFunding-child
    1000 Förderer National Institute of Biomedical Imaging and Bioengineering |
    1000 Förderprogramm -
    1000 Fördernummer 1U01EB022546
  17. 1000 joinedFunding-child
    1000 Förderer Department of Biological Sciences at Rensselaer Polytechnic Institute |
    1000 Förderprogramm -
    1000 Fördernummer -
  18. 1000 joinedFunding-child
    1000 Förderer JSPS KAKENHI |
    1000 Förderprogramm -
    1000 Fördernummer JP26293048
  19. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft (DFG) |
    1000 Förderprogramm -
    1000 Fördernummer SFB740/D2; TRR186/A17
  20. 1000 joinedFunding-child
    1000 Förderer National Institute of Diabetes and Digestive and Kidney Diseases |
    1000 Förderprogramm -
    1000 Fördernummer DK097164
  21. 1000 joinedFunding-child
    1000 Förderer Canadian Institutes of Health Research |
    1000 Förderprogramm -
    1000 Fördernummer -
  22. 1000 joinedFunding-child
    1000 Förderer Heart and Stroke Foundation of Canada |
    1000 Förderprogramm -
    1000 Fördernummer -
  23. 1000 joinedFunding-child
    1000 Förderer Dutch Foundation for Technology and Science (STW) |
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1000 Erstellt am 2018-10-25T14:34:19.491+0200
1000 Erstellt von 122
1000 beschreibt frl:6410802
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2021-01-05T09:37:43.475+0100
1000 Objekt bearb. Tue Jan 05 09:37:43 CET 2021
1000 Vgl. frl:6410802
1000 Oai Id
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1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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