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

NucPred

Fetching Q9NXG0 from www.uniprot.org...

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

   1  MAARSPPSPHPSPPARQLGPRSPRVGRGAEVHAMRSEASGFAGAAREVVA    50
  51  DESDKIWVGEEGSGGRRGPGGAAPAHAPLLSAPMGSRRLEGISVEEAMVT   100
 101  RTQLLEEELSSLKEELALCQADKEFVWSLWKRLQVTNPDLTQVVSLVVER   150
 151  EKQKSEAKDRKVLEILQVKDAKIQEFEQRESVLKQEINDLVKRKIAVDEE   200
 201  NAFLRKEFSDLEKKFKDKSQEIKDTKECVQNKEEQNRLVIKNLEEENKKL   250
 251  STRCTDLLNDLEKLRKQEAHLRKEKYSTDAKIKTFEDNLIEARKEVEVSQ   300
 301  SKYNALSLQLSNKQTELIQKDMDITLVRKELQELQNLYKQNSTHTAQQAE   350
 351  LIQQLQVLNMDTQKVLRNQEDVHTAESISYQKLYNELHICFETTKSNEAM   400
 401  LRQSVTNLQDQLLQKEQENAKLKEKLQESQGAPLPLPQESDPDYSAQVPH   450
 451  RPSLSSLETLMVSQKSEIEYLQEKLKIANEKLSENISANKGFSRKSIMTS   500
 501  AEGKHKEPPVKRSRSLSPKSSFTDSEELQKLRKAERKIENLEKALQLKSQ   550
 551  ENDELRDAHEKRKERLQMLQTNYRAVKEQLKQWEEGSGMTEIRKIKRADP   600
 601  QQLRQEDSDAVWNELAYFKRENQELMIQKMNLEEELDELKVHISIDKAAI   650
 651  QELNRCVAERREEQLFRSGEDDEVKRSTPEKNGKEMLEQTLQKVTELENR   700
 701  LKSFEKRSRKLKEGNKKLMKENDFLKSLLKQQQEDTETREKELEQIIKGS   750
 751  KDVEKENTELQVKISELETEVTSLRRQVAEANALRNENEELINPMEKSHQ   800
 801  SADRAKSEMATMKVRSGRYDCKTTMTKVKFKAAKKNCSVGRHHTVLNHSI   850
 851  KVMSNVFENLSKDGWEDVSESSSDSEAQTSQTLGTIIVETSQKISPTEDG   900
 901  KDQKESDPTEDSQTQGKEIVQTYLNIDGKTPKDYFHDKNAKKPTFQKKNC   950
 951  KMQKSSHTAVPTRVNREKYKNITAQKSSSNIILLRERIISLQQQNSVLQN  1000
1001  AKKTAELSVKEYKEVNEKLLHQQQVSDQRFQTSRQTIKKLNLDLAGLRKE  1050
1051  KEDLLKKLESSSEITSLAEENSQVTFPRIQVTSLSPSRSMDLEMKQLQYK  1100
1101  LKNATNELTKQSSNVKTLKFELLAKEEHIKEMHEKISRMERDITMKRHLI  1150
1151  EDLKFRQKVNLESNKSFSEMLQNLDKKVKTLTEECSNKKVSIDSLKQRLN  1200
1201  VAVKEKSQYEQMYQKSKEELEKKDLKLTLLVSRISETESAMAEIETAASK  1250
1251  QLQELALQSEQVLEGAQKTLLLANEKVEEFTTFVKALAKELQNDVHVVRR  1300
1301  QIRELKKMKKNRDACKTSTHKAQTLAASILNISRSDLEEILDTEDQVEIE  1350
1351  KTKIDAENDKEWMLYIQKLLEGQSLTLSPRLKCNGAIVAHQNLRLPDSSS  1400
1401  SASAS                                               1405

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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