SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P82279 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MALKNINYLLIFYLSFSLLIYIKNSFCNKNNTRCLSNSCQNNSTCKDFSK    50
  51  DNDCSCSDTANNLDKDCDNMKDPCFSNPCQGSATCVNTPGERSFLCKCPP   100
 101  GYSGTICETTIGSCGKNSCQHGGICHQDPIYPVCICPAGYAGRFCEIDHD   150
 151  ECASSPCQNGAVCQDGIDGYSCFCVPGYQGRHCDLEVDECASDPCKNEAT   200
 201  CLNEIGRYTCICPHNYSGVNCELEIDECWSQPCLNGATCQDALGAYFCDC   250
 251  APGFLGDHCELNTDECASQPCLHGGLCVDGENRYSCNCTGSGFTGTHCET   300
 301  LMPLCWSKPCHNNATCEDSVDNYTCHCWPGYTGAQCEIDLNECNSNPCQS   350
 351  NGECVELSSEKQYGRITGLPSSFSYHEASGYVCICQPGFTGIHCEEDVNE   400
 401  CSSNPCQNGGTCENLPGNYTCHCPFDNLSRTFYGGRDCSDILLGCTHQQC   450
 451  LNNGTCIPHFQDGQHGFSCLCPSGYTGSLCEIATTLSFEGDGFLWVKSGS   500
 501  VTTKGSVCNIALRFQTVQPMALLLFRSNRDVFVKLELLSGYIHLSIQVNN   550
 551  QSKVLLFISHNTSDGEWHFVEVIFAEAVTLTLIDDSCKEKCIAKAPTPLE   600
 601  SDQSICAFQNSFLGGLPVGMTSNGVALLNFYNMPSTPSFVGCLQDIKIDW   650
 651  NHITLENISSGSSLNVKAGCVRKDWCESQPCQSRGRCINLWLSYQCDCHR   700
 701  PYEGPNCLREYVAGRFGQDDSTGYVIFTLDESYGDTISLSMFVRTLQPSG   750
 751  LLLALENSTYQYIRVWLERGRLAMLTPNSPKLVVKFVLNDGNVHLISLKI   800
 801  KPYKIELYQSSQNLGFISASTWKIEKGDVIYIGGLPDKQETELNGGFFKG   850
 851  CIQDVRLNNQNLEFFPNPTNNASLNPVLVNVTQGCAGDNSCKSNPCHNGG   900
 901  VCHSRWDDFSCSCPALTSGKACEEVQWCGFSPCPHGAQCQPVLQGFECIA   950
 951  NAVFNGQSGQILFRSNGNITRELTNITFGFRTRDANVIILHAEKEPEFLN  1000
1001  ISIQDSRLFFQLQSGNSFYMLSLTSLQSVNDGTWHEVTLSMTDPLSQTSR  1050
1051  WQMEVDNETPFVTSTIATGSLNFLKDNTDIYVGDRAIDNIKGLQGCLSTI  1100
1101  EIGGIYLSYFENVHGFINKPQEEQFLKISTNSVVTGCLQLNVCNSNPCLH  1150
1151  GGNCEDIYSSYHCSCPLGWSGKHCELNIDECFSNPCIHGNCSDRVAAYHC  1200
1201  TCEPGYTGVNCEVDIDNCQSHQCANGATCISHTNGYSCLCFGNFTGKFCR  1250
1251  QSRLPSTVCGNEKTNLTCYNGGNCTEFQTELKCMCRPGFTGEWCEKDIDE  1300
1301  CASDPCVNGGLCQDLLNKFQCLCDVAFAGERCEVDLADDLISDIFTTIGS  1350
1351  VTVALLLILLLAIVASVVTSNKRATQGTYSPSRQEKEGSRVEMWNLMPPP  1400
1401  AMERLI                                              1406

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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