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

NucPred

Fetching Q13224 from www.uniprot.org...

The NucPred score for your sequence is 0.68 (see score help below)

   1  MKPRAECCSPKFWLVLAVLAVSGSRARSQKSPPSIGIAVILVGTSDEVAI    50
  51  KDAHEKDDFHHLSVVPRVELVAMNETDPKSIITRICDLMSDRKIQGVVFA   100
 101  DDTDQEAIAQILDFISAQTLTPILGIHGGSSMIMADKDESSMFFQFGPSI   150
 151  EQQASVMLNIMEEYDWYIFSIVTTYFPGYQDFVNKIRSTIENSFVGWELE   200
 201  EVLLLDMSLDDGDSKIQNQLKKLQSPIILLYCTKEEATYIFEVANSVGLT   250
 251  GYGYTWIVPSLVAGDTDTVPAEFPTGLISVSYDEWDYGLPARVRDGIAII   300
 301  TTAASDMLSEHSFIPEPKSSCYNTHEKRIYQSNMLNRYLINVTFEGRNLS   350
 351  FSEDGYQMHPKLVIILLNKERKWERVGKWKDKSLQMKYYVWPRMCPETEE   400
 401  QEDDHLSIVTLEEAPFVIVESVDPLSGTCMRNTVPCQKRIVTENKTDEEP   450
 451  GYIKKCCKGFCIDILKKISKSVKFTYDLYLVTNGKHGKKINGTWNGMIGE   500
 501  VVMKRAYMAVGSLTINEERSEVVDFSVPFIETGISVMVSRSNGTVSPSAF   550
 551  LEPFSADVWVMMFVMLLIVSAVAVFVFEYFSPVGYNRCLADGREPGGPSF   600
 601  TIGKAIWLLWGLVFNNSVPVQNPKGTTSKIMVSVWAFFAVIFLASYTANL   650
 651  AAFMIQEEYVDQVSGLSDKKFQRPNDFSPPFRFGTVPNGSTERNIRNNYA   700
 701  EMHAYMGKFNQRGVDDALLSLKTGKLDAFIYDAAVLNYMAGRDEGCKLVT   750
 751  IGSGKVFASTGYGIAIQKDSGWKRQVDLAILQLFGDGEMEELEALWLTGI   800
 801  CHNEKNEVMSSQLDIDNMAGVFYMLGAAMALSLITFICEHLFYWQFRHCF   850
 851  MGVCSGKPGMVFSISRGIYSCIHGVAIEERQSVMNSPTATMNNTHSNILR   900
 901  LLRTAKNMANLSGVNGSPQSALDFIRRESSVYDISEHRRSFTHSDCKSYN   950
 951  NPPCEENLFSDYISEVERTFGNLQLKDSNVYQDHYHHHHRPHSIGSASSI  1000
1001  DGLYDCDNPPFTTQSRSISKKPLDIGLPSSKHSQLSDLYGKFSFKSDRYS  1050
1051  GHDDLIRSDVSDISTHTVTYGNIEGNAAKRRKQQYKDSLKKRPASAKSRR  1100
1101  EFDEIELAYRRRPPRSPDHKRYFRDKEGLRDFYLDQFRTKENSPHWEHVD  1150
1151  LTDIYKERSDDFKRDSVSGGGPCTNRSHIKHGTGDKHGVVSGVPAPWEKN  1200
1201  LTNVEWEDRSGGNFCRSCPSKLHNYSTTVTGQNSGRQACIRCEACKKAGN  1250
1251  LYDISEDNSLQELDQPAAPVAVTSNASTTKYPQSPTNSKAQKKNRNKLRR  1300
1301  QHSYDTFVDLQKEEAALAPRSVSLKDKGRFMDGSPYAHMFEMSAGESTFA  1350
1351  NNKSSVPTAGHHHHNNPGGGYMLSKSLYPDRVTQNPFIPTFGDDQCLLHG  1400
1401  SKSYFFRQPTVAGASKARPDFRALVTNKPVVSALHGAVPARFQKDICIGN  1450
1451  QSNPCVPNNKNPRAFNGSSNGHVYEKLSSIESDV                  1484

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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