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Negative training samples are also important for mining microRNAs from genome-scale data

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Negative training samples are also important for mining microRNAs from genome-scale data BY Leyi Wei microRNA microRNA precursor 1 microRNA ... – PowerPoint PPT presentation

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Title: Negative training samples are also important for mining microRNAs from genome-scale data


1
Negative training samples are also important for
mining microRNAs from genome-scale data
  • BY Leyi
    Wei

2
????
  • microRNA ? microRNA precursor
  • (1)microRNA????????22nt????RNA,?????????,??????
    ?????????,??microRNA?????
  • (2)microRNA precursor(pre-miRNA)
    ?????microRNA? ????microRNA?pre-miRNA?????
    pre-miRNA???microRNA? ???????????,???????Pre-miRNA
    ?????????????(hairpin)???

3
The pathway of microRNA in mammals

4
??microRNA???
  • Comparative methods
  • ?????? ,?????????,? ??????microRNA
  • Non -- comparative methods
  • ????????????????, ????????microRNA

5
?????????
  • 1. ??? ? ??
  • ???????????????????????
  • ????????????
  • ???
  • ???????????????,?????????
    ?????????????????(real pre-miRNA)??? (pseudo
    pre-miRNA)????

6
  • ?? ????????real pre-miRNA ???
  • ?? ???pseudo pre-miRNA???,??????????????????,?
    ????????????real pre-miRNA?????,????????????

7
??????????????
  • ?????????????????
  • ?????????????????,??????????????????CDS????????
    ?,???????????????????????????

8
(????)??????????
9
  • ROC- analysis

10
????
  1. ?????????,???????????????,?????????
  2. ???????,??????????,???????????????????????????????
    ?????

11
???????????
  • Triplet-SVM classifier

12
???????????
  • Mirident-classifier (Table)

13
Mirident-classifier (Figure)
14
Our ensemble classifier based on this negative set
  • Our ensemble classifier performance
  • ???? ??????????,?????????????,?????????
  • Feature set performance
  • ???? ????????????????,???????????,??????????
    ??????

15
mirnaDetect
  • ?????????????,??????????,??????????????pre-miRNA??
    ?

16
mirnaDetect
  • ????

17
????
  • ??????,???????????,???????????????
  • ?????????(SCI)
  • (1)??? ????
  • ???, ?????????????????????,
    ???,????,?????????????????????????,???????????????
    ?????,??????(???????,????????)?
  • ???????????????,???????????

18
  • (2)?????
  • ??? ???,??????????????????,????????????,???????
    ????
  • (3)???????cover letter .
  • ??????????

19
  • (4) ???????
  • ?????????????,????????????????????????????????
    under review?
  • ??????,?????
  • ?????,???????responding author

20
  • (5)??????!
  • Rejected OR (major)Revision
  • (6)Revision
  • ???????? ?????Editor?? Riviewers
    ????????????????,?????????????????manuscript??,???
    ??????????,?????The Rebuttal Letter
  • ????????
  • ????????

21
(No Transcript)
22
  • ??Revised manuscript
  • ?????????????,????Track Changes File?
  • ???????,??????????????,??????????

23
  • ????!
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