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

NucPred

Fetching O55005 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MKWKHLPLLVMISLLTLSKKHLLLAQLIPDPEDLERGNDNGTPAPTSDND    50
  51  DNSLGYTGSRLRQEDFPPRIVEHPSDLIVSKGEPATLNCKAEGRPTPTIE   100
 101  WYKGGERVETDKDDPRSHRMLLPSGSLFFLRIVHGRKSRPDEGVYICVAR   150
 151  NYLGEAVSHNASLEVAILRDDFRQNPSDVMVAVGEPAVMECQPPRGHPEP   200
 201  TISWKKDGSPLDDKDERITIRGGKLMITYTRKSDAGKYVCVGTNMVGERE   250
 251  SKVADVTVLERPSFVKRPSNLAVTVDDSAEFKCEARGDPVPTFGWRKDDG   300
 301  ELPKSRYEIRDDHTLKIRKVTAGDMGSYTCVAENMVGKAEASATLTVQEP   350
 351  PHFVVKPRDQVVALGRTVTFQCEATGNPQPAIFWRREGSQNLLFSYQPPQ   400
 401  SSSRFSVSQTGDLTVTNVQRSDVGYYICQTLNVAGSIITKAYLEVTDVIA   450
 451  DRPPPVIRQGPVNQTVAVDGTLTLSCVATGSPVPTILWRKDGVLVSTQDS   500
 501  RIKQLESGVLQIRYAKLGDTGRYTCTASTPSGEATWSAYIEVQEFGVPVQ   550
 551  PPRPTDPNLIPSAPSKPEVTDVSKNTVTLLWQPNLNSGATPTSYIIEAFS   600
 601  HASGSSWQTVAENVKTETFAIKGLKPNAIYLFLVRAANAYGISDPSQISD   650
 651  PVKTQDVPPTTQGVDHKQVQRELGNVVLHLHNPTILSSSSVEVHWTVDQQ   700
 701  SQYIQGYKILYRPSGASHGESEWLVFEVRTPTKNSVVIPDLRKGVNYEIK   750
 751  ARPFFNEFQGADSEIKFAKTLEERPSAPPRSVTVSKNDGNGTAILVTWQP   800
 801  PPEDTQNGMVQEYKVWCLGNETRYHINKTVDGSTFSVVIPFLVPGIRYSV   850
 851  EVAASTGAGPGVKSEPQFIQLDSHGNPVSPEDQVSLAQQISDVVKQPAFI   900
 901  AGIGAACWIILMVFSIWLYRHRKKRNGLSSTYAGIRKVPSFTFTPTVTYQ   950
 951  RGGEAVSSGGRPGLLNISEPATQPWLADTWPNTGNSHNDCSINCCTASNG  1000
1001  NSDSNLTTYSRPADCIANYNNQLDNKQTNLMLPESTVYGDVDLSNKINEM  1050
1051  KTFNSPNLKDGRFVNPSGQPTPYATTQLIQANLINNMNNGGGDSSEKHWK  1100
1101  PPGQQKQEVAPIQYNIMEQNKLNKDYRANDTILPTIPYNHSYDQNTGGSY  1150
1151  NSSDRGSSTSGSQGHKKGARTPKAPKQGGMNWADLLPPPPAHPPPHSNSE  1200
1201  EYSMSVDESYDQEMPCPVPPARMYLQQDELEEEEAERGPTPPVRGAASSP  1250
1251  AAVSYSHQSTATLTPSPQEELQPMLQDCPEDLGHMPHPPDRRRQPVSPPP  1300
1301  PPRPISPPHTYGYISGPLVSDMDTDAPEEEEDEADMEVAKMQTRRLLLRG  1350
1351  LEQTPASSVGDLESSVTGSMINGWGSASEEDNISSGRSSVSSSDGSFFTD  1400
1401  ADFAQAVAAAAEYAGLKVARRQMQDAAGRRHFHASQCPRPTSPVSTDSNM  1450
1451  SAAVIQKARPTKKQKHQPGHLRREAYTDDLPPPPVPPPAIKSPSVQSKAQ  1500
1501  LEARPIMGPKLASIEARADRSSDRKGGSYKGREALDGRQVTDLRTSPGDP  1550
1551  REAQEQPNEGKARGTKTAKRDLPPAKTHLIPEDILPYCRPTFPTSNNPRD  1600
1601  PSSSSSMSSRGSGSRQREQANVGRRNMAEMQVLGGFERGDENNEELEETE  1650
1651  S                                                   1651

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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