Genome-scale MicroRNA target prediction through clustering with Dirichlet process mixture model

References 48

1. 1.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

2. 2.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

3. 3.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

4. 4.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

5. 5.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

6. 6.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

7. 7.
   Survey of Computational Algorithms for MicroRNA Target Prediction · 2009

   No notice
8. 8.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

9. 9.

   This reference’s wording can’t be shown under the paper’s licence.

   Not in our library

10. 10.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

11. 11.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

12. 12.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

13. 13.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

14. 14.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

15. 15.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

16. 16.
    Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites · 2010

    No notice
17. 17.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

18. 18.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

19. 19.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

20. 20.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

21. 21.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

22. 22.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

23. 23.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

24. 24.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

25. 25.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

26. 26.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

27. 27.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

28. 28.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

29. 29.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

30. 30.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

31. 31.
    miRDB: an online resource for microRNA target prediction and functional annotations · 2014

    No notice
32. 32.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

33. 33.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

34. 34.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

35. 35.
    Mapping the Human miRNA Interactome by CLASH Reveals Frequent Noncanonical Binding · 2013

    No notice
36. 36.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

37. 37.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

38. 38.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

39. 39.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

40. 40.

    This reference’s wording can’t be shown under the paper’s licence.

    Not in our library

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