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

NucPred

Fetching Q8N7X0 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MASKQTKKKEVHRINSAHGSDKSKDFYPFGSNVQSGSTEQKKGKFPLWPE    50
  51  WSEADINSEKWDAGKGAKEKDKTGKSPVFHFFEDPEGKIELPPSLKIYSW   100
 101  KRPQDILFSQTPVVVKNEITFDLFSANEHLLCSELMRWIISEIYAVWKIF   150
 151  NGGILSNYFKGTSGEPPLLPWKPWEHIYSLCKAVKGHMPLFNSYGKYVVK   200
 201  LYWMGCWRKITIDDFLPFDEDNNLLLPATTYEFELWPMLLSKAIIKLANI   250
 251  DIHVADRRELGEFTVIHALTGWLPEVISLHPGYMDKVWELLKEILPEFKL   300
 301  SDEASSESKIAVLDSKLKEPGKEGKEGKEIKDGKEVKDVKEFKPESSLTT   350
 351  LKAPEKSDKVPKEKADARDIGKKRSKDGEKEKFKFSLHGSRPSSEVQYSV   400
 401  QSLSDCSSAIQTSHMVVYATFTPLYLFENKIFSLEKMADSAEKLREYGLS   450
 451  HICSHPVLVTRSRSCPLVAPPKPPPLPPWKLIRQKKETVITDEAQELIVK   500
 501  KPERFLEISSPFLNYRMTPFTIPTEMHFVRSLIKKGIPPGSDLPSVSETD   550
 551  ETATHSQTDLSQITKATSQGNTASQVILGKGTDEQTDFGLGDAHQSDGLN   600
 601  LEREIVSQTTATQEKSQEELPTTNNSVSKEIWLDFEDFCVCFQNIYIFHK   650
 651  PSSYCLNFQKSEFKFSEERVSYYLFVDSLKPIELLVCFSALVRWGEYGAL   700
 701  TKDSPPIEPGLLTAETFSWKSLKPGSLVLKIHTYATKATVVRLPVGRHML   750
 751  LFNAYSPVGHSIHICSMVSFVIGDEHVVLPNFEPESCRFTEQSLLIMKAI   800
 801  GNVIANFKDKGKLSAALKDLQTAHYPVPFHDKELTAQHFRVFHLSLWRLM   850
 851  KKVQITKPPPNFKFAFRAMVLDLELLNSSLEEVSLVEWLDVKYCMPTSDK   900
 901  EYSAEEVAAAIKIQAMWRGTYVRLLMKARIPDTKENISVADTLQKVWAVL   950
 951  EMNLEQYAVSLLRLMFKSKCKSLESYPCYQDEETKIAFADYTVTYQEQPP  1000
1001  NSWFIVFRETFLVHQDMILVPKVYTTLPICILHIVNNDTMEQVPKVFQKV  1050
1051  VPYLYTKNKKGYTFVAEAFTGDTYVAASRWKLRLIGSSAPLPCLSRDSPC  1100
1101  NSFAIKEIRDYYIPNDKKILFRYSVKVLTPQPATIQVRTSKPDAFIKLQV  1150
1151  LENEETMVSSTGKGQAIIPAFHFLKSEKGLSSQSSKHILSFHSASKKEQE  1200
1201  VYVKKKAAQGIQKSPKGRAVSAIQDIGLPLVEEETTSTPTREDSSSTPLQ  1250
1251  NYKYIIQCSVLYNSWPLTESQLTFVQALKDLKKSNTKAYGERHEELINLG  1300
1301  SPDSHTISEGQKSSVTSKTTRKGKEKSSEKEKTAKEKQAPRFEPQISTVH  1350
1351  PQQEDPNKPYWILRLVTEHNESELFEVKKDTERADEIRAMKQAWETTEPG  1400
1401  RAIKASQARLHYLSGFIKKTSDAESPPISESQTKPKEEVETAARGVKEPN  1450
1451  SKNSAGSESKEMTQTGSGSAVWKKWQLTKGLRDVAKSTSSESGGVSSPGK  1500
1501  EEREQSTRKENIQTGPRTRSPTILETSPRLIRKALEFMDLSQYVRKTDTD  1550
1551  PLLQTDELNQQQAMQKAEEIHQFRQHRTRVLSIRNIDQEERLKLKDEVLD  1600
1601  MYKEMQDSLDEARQKIFDIREEYRNKLLEAEHLKLETLAAQEAAMKLETE  1650
1651  KMTPAPDTQKKKKGKKK                                   1667

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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