Cited by 1,739

A Pattern-Based Method for the Identification of MicroRNA Binding Sites and Their Corresponding Heteroduplexes

Miranda, Kevin C., Huynh, Tien, Tay, Yvonne, Ang, Yen-Sin, Tam, Wai-Leong, Thomson, Andrew M., Lim, Bing, Rigoutsos, Isidore·2006·Cell

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cell.2006.07.031

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Part of this paper’s reference list could not be split into single entries.

Flagged first, then by citations

Research works printed but not linked: 43

  1. [1]1. Altschul, S.F. ∙ Gish, W. Local alignment statistics Methods Enzymol. 1996; 266:460-480 Crossref Scopus (0) PubMed Google Scholar
  2. [4]4. Brazma, A. ∙ Jonassen, I. ∙ Eidhammer, I. ... Approaches to the automatic discovery of patterns in biosequences J. Comput. Biol. 1998; 5:279-305 Crossref Scopus (192) PubMed Google Scholar
  3. [5]5. Brennecke, J. ∙ Hipfner, D.R. ∙ Stark, A. ... bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila Cell. 2003; 113:25-36 Full Text Full Text (PDF) Scopus (1748) PubMed Google Scholar
  4. [6]6. Brennecke, J. ∙ Stark, A. ∙ Russell, R.B. ... Principles of microRNA-target recognition PLoS Biol. 2005; 3:e85 Crossref Scopus (1918) PubMed Google Scholar
  5. [7]7. Croce, C.M. ∙ Calin, G.A. miRNAs, cancer, and stem cell division Cell. 2005; 122:6-7 Full Text Full Text (PDF) Scopus (1258) PubMed Google Scholar
  6. [8]8. Darzentas, N. ∙ Rigoutsos, I. ∙ Ouzounis, C.A. Sensitive detection of sequence similarity using combinatorial pattern discovery: a challenging study of two distantly related protein families Proteins. 2005; 61:926-937 Crossref Scopus (7) PubMed Google Scholar
  7. [9]9. Doolittle, R.F. ∙ Hunkapiller, M.W. ∙ Hood, L.E. ... Simian sarcoma virus onc gene, v-sis, is derived from the gene (or genes) encoding a platelet-derived growth factor Science. 1983; 221:275-277 Crossref Scopus (1057) PubMed Google Scholar
  8. [10]10. Enright, A.J. ∙ John, B. ∙ Gaul, U. ... MicroRNA targets in Drosophila Genome Biol. 2003; 5:R1 Crossref Scopus (2735) PubMed Google Scholar
  9. [11]11. Ettwiller, L.M. ∙ Rung, J. ∙ Birney, E. Discovering novel cis-regulatory motifs using functional networks Genome Res. 2003; 13:883-895 Crossref Scopus (18) PubMed Google Scholar
  10. [12]12. Filipowicz, W. RNAi: the nuts and bolts of the RISC machine Cell. 2005; 122:17-20 Full Text Full Text (PDF) Scopus (431) PubMed Google Scholar
  11. [13]13. Griffiths-Jones, S. ∙ Bateman, A. ∙ Marshall, M. ... Rfam: an RNA family database Nucleic Acids Res. 2003; 31:439-441 Crossref Scopus (1215) PubMed Google Scholar
  12. [14]14. Gusfield, D. Algorithms on strings, trees, and sequences: computer science and computational biology Cambridge University Press, Cambridge, UK; New York, NY, 1997 Crossref Google Scholar
  13. [15]15. Hammond, S.M. Dicing and slicing: the core machinery of the RNA interference pathway FEBS Lett. 2005; 579:5822-5829 Crossref Scopus (443) PubMed Google Scholar
  14. [16]16. Hannon, G.J. RNA interference Nature. 2002; 418:244-251 Crossref Scopus (3652) PubMed Google Scholar
  15. [17]17. Hobert, O. Common logic of transcription factor and microRNA action Trends Biochem. Sci. 2004; 29:462-468 Full Text Full Text (PDF) Scopus (175) PubMed Google Scholar
  16. [18]18. Hofacker, I.L. ∙ Fontana, W. ∙ Stadler, P. ... Fast folding and comparison of RNA secondary structures Monatshefte f Chemie. 1994; 125:167-188 Crossref Scopus (1837) Google Scholar
  17. [19]19. John, B. ∙ Enright, A.J. ∙ Aravin, A. ... Human MicroRNA targets PLoS Biol. 2004; 2:e363 Crossref Scopus (3099) PubMed Google Scholar
  18. [20]20. Johnston, R.J. ∙ Hobert, O. A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans Nature. 2003; 426:845-849 Crossref Scopus (621) PubMed Google Scholar
  19. [21]21. Karlin, S. ∙ Altschul, S.F. Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes Proc. Natl. Acad. Sci. USA. 1990; 87:2264-2268 Crossref Scopus (1211) PubMed Google Scholar
  20. [22]22. Kawai, K. ∙ Yokota, C. ∙ Ohashi, S. ... Evidence that glucagon stimulates insulin secretion through its own receptor in rats Diabetologia. 1995; 38:274-276 Crossref Scopus (84) PubMed Google Scholar
  21. [23]23. Kiriakidou, M. ∙ Nelson, P.T. ∙ Kouranov, A. ... A combined computational-experimental approach predicts human microRNA targets Genes Dev. 2004; 18:1165-1178 Crossref Scopus (650) PubMed Google Scholar
  22. [24]24. Krek, A. ∙ Grun, D. ∙ Poy, M.N. ... Combinatorial microRNA target predictions Nat. Genet. 2005; 37:495-500 Crossref Scopus (4021) PubMed Google Scholar
  23. [25]25. Lagos-Quintana, M. ∙ Rauhut, R. ∙ Lendeckel, W. ... Identification of novel genes coding for small expressed RNAs Science. 2001; 294:853-858 Crossref Scopus (4148) PubMed Google Scholar
  24. [26]26. Lagos-Quintana, M. ∙ Rauhut, R. ∙ Meyer, J. ... New microRNAs from mouse and human RNA. 2003; 9:175-179 Crossref Scopus (762) PubMed Google Scholar
  25. [27]27. Lee, R.C. ∙ Ambros, V. An extensive class of small RNAs in Caenorhabditis elegans Science. 2001; 294:862-864 Crossref Scopus (2405) PubMed Google Scholar
  26. [28]28. Lewis, B.P. ∙ Burge, C.B. ∙ Bartel, D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets Cell. 2005; 120:15-20 Full Text Full Text (PDF) Scopus (10289) PubMed Google Scholar
  27. [29]29. Lewis, B.P. ∙ Shih, I.H. ∙ Jones-Rhoades, M.W. ... Prediction of mammalian microRNA targets Cell. 2003; 115:787-798 Full Text Full Text (PDF) Scopus (4386) PubMed Google Scholar
  28. [30]30. MacDonald, P.E. ∙ Ha, X.F. ∙ Wang, J. ... Members of the Kv1 and Kv2 voltage-dependent K(+) channel families regulate insulin secretion Mol. Endocrinol. 2001; 15:1423-1435 Crossref Scopus (168) PubMed Google Scholar
  29. [32]32. Moss, E.G. ∙ Lee, R.C. ∙ Ambros, V. The cold shock domain protein LIN-28 controls developmental timing in C. elegans and is regulated by the lin-4 RNA Cell. 1997; 88:637-646 Full Text Full Text (PDF) Scopus (714) PubMed Google Scholar
  30. [33]33. Murphy, E. ∙ Rigoutsos, I. ∙ Shibuya, T. ... Reevaluation of human cytomegalovirus coding potential Proc. Natl. Acad. Sci. USA. 2003; 100:13585-13590 Crossref Scopus (155) PubMed Google Scholar
  31. [34]34. Neduva, V. ∙ Linding, R. ∙ Su-Angrand, I. ... Systematic discovery of new recognition peptides mediating protein interaction networks PLoS Biol. 2005; 3:e405 Crossref Scopus (269) PubMed Google Scholar
  32. [35]35. Pesole, G. ∙ Grillo, G. ∙ Larizza, A. ... The untranslated regions of eukaryotic mRNAs: structure, function, evolution and bioinformatic tools for their analysis Brief. Bioinform. 2000; 1:236-249 Crossref Scopus (60) PubMed Google Scholar
  33. [36]36. Poy, M.N. ∙ Eliasson, L. ∙ Krutzfeldt, J. ... A pancreatic islet-specific microRNA regulates insulin secretion Nature. 2004; 432:226-230 Crossref Scopus (1824) PubMed Google Scholar
  34. [38]38. Rajewsky, N. ∙ Socci, N.D. Computational identification of microRNA targets Dev. Biol. 2004; 267:529-535 Crossref Scopus (249) PubMed Google Scholar
  35. [39]39. Rehmsmeier, M. ∙ Steffen, P. ∙ Hochsmann, M. ... Fast and effective prediction of microRNA/target duplexes RNA. 2004; 10:1507-1517 Crossref Scopus (2028) PubMed Google Scholar
  36. [40]40. Reinhart, B.J. ∙ Slack, F.J. ∙ Basson, M. ... The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans Nature. 2000; 403:901-906 Crossref Scopus (3973) PubMed Google Scholar
  37. [41]41. Rigoutsos, I. ∙ Floratos, A. Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm Bioinformatics. 1998; 14:55-67 Crossref Scopus (419) PubMed Google Scholar
  38. [42]42. Rigoutsos, I. ∙ Huynh, T. ∙ Floratos, A. ... Dictionary-driven protein annotation Nucleic Acids Res. 2002; 30:3901-3916 Crossref Scopus (26) PubMed Google Scholar
  39. [43]43. Rigoutsos, I. ∙ Huynh, T. ∙ Miranda, K. ... Short blocks from the noncoding parts of the human genome have instances within nearly all known genes and relate to biological processes Proc. Natl. Acad. Sci. USA. 2006; 103:6605-6610 Crossref Scopus (98) PubMed Google Scholar
  40. [44]44. Rigoutsos, I. ∙ Riek, P. ∙ Graham, R.M. ... Structural details (kinks and non-alpha conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors Nucleic Acids Res. 2003; 31:4625-4631 Crossref Scopus (26) PubMed Google Scholar
  41. [45]45. Schratt, G.M. ∙ Tuebing, F. ∙ Nigh, E.A. ... A brain-specific microRNA regulates dendritic spine development Nature. 2006; 439:283-289 Crossref Scopus (1544) PubMed Google Scholar
  42. [46]46. Shibuya, T. ∙ Rigoutsos, I. Dictionary-driven prokaryotic gene finding Nucleic Acids Res. 2002; 30:2710-2725 Crossref Scopus (29) PubMed Google Scholar
  43. [47]47. Stark, A. ∙ Brennecke, J. ∙ Russell, R.B. ... Identification of Drosophila MicroRNA targets PLoS Biol. 2003; 1:e60 Crossref Scopus (642) PubMed Google Scholar

Cited by

Sorted by citations

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review