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

NucPred

Fetching Q14152 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MPAYFQRPENALKRANEFLEVGKKQPALDVLYDVMKSKKHRTWQKIHEPI    50
51 MLKYLELCVDLRKSHLAKEGLYQYKNICQQVNIKSLEDVVRAYLKMAEEK 100
101 TEAAKEESQQMVLDIEDLDNIQTPESVLLSAVSGEDTQDRTDRLLLTPWV 150
151 KFLWESYRQCLDLLRNNSRVERLYHDIAQQAFKFCLQYTRKAEFRKLCDN 200
201 LRMHLSQIQRHHNQSTAINLNNPESQSMHLETRLVQLDSAISMELWQEAF 250
251 KAVEDIHGLFSLSKKPPKPQLMANYYNKVSTVFWKSGNALFHASTLHRLY 300
301 HLSREMRKNLTQDEMQRMSTRVLLATLSIPITPERTDIARLLDMDGIIVE 350
351 KQRRLATLLGLQAPPTRIGLINDMVRFNVLQYVVPEVKDLYNWLEVEFNP 400
401 LKLCERVTKVLNWVREQPEKEPELQQYVPQLQNNTILRLLQQVSQIYQSI 450
451 EFSRLTSLVPFVDAFQLERAIVDAARHCDLQVRIDHTSRTLSFGSDLNYA 500
501 TREDAPIGPHLQSMPSEQIRNQLTAMSSVLAKALEVIKPAHILQEKEEQH 550
551 QLAVTAYLKNSRKEHQRILARRQTIEERKERLESLNIQREKEELEQREAE 600
601 LQKVRKAEEERLRQEAKEREKERILQEHEQIKKKTVRERLEQIKKTELGA 650
651 KAFKDIDIEDLEELDPDFIMAKQVEQLEKEKKELQERLKNQEKKIDYFER 700
701 AKRLEEIPLIKSAYEEQRIKDMDLWEQQEEERITTMQLEREKALEHKNRM 750
751 SRMLEDRDLFVMRLKAARQSVYEEKLKQFEERLAEERHNRLEERKRQRKE 800
801 ERRITYYREKEEEEQRRAEEQMLKEREERERAERAKREEELREYQERVKK 850
851 LEEVERKKRQRELEIEERERRREEERRLGDSSLSRKDSRWGDRDSEGTWR 900
901 KGPEADSEWRRGPPEKEWRRGEGRDEDRSHRRDEERPRRLGDDEDREPSL 950
951 RPDDDRVPRRGMDDDRGPRRGPEEDRFSRRGADDDRPSWRNTDDDRPPRR 1000
1001 IADEDRGNWRHADDDRPPRRGLDEDRGSWRTADEDRGPRRGMDDDRGPRR 1050
1051 GGADDERSSWRNADDDRGPRRGLDDDRGPRRGMDDDRGPRRGMDDDRGPR 1100
1101 RGMDDDRGPRRGLDDDRGPWRNADDDRIPRRGAEDDRGPWRNMDDDRLSR 1150
1151 RADDDRFPRRGDDSRPGPWRPLVKPGGWREKEKAREESWGPPRESRPSEE 1200
1201 REWDREKERDRDNQDREENDKDPERERDRERDVDREDRFRRPRDEGGWRR 1250
1251 GPAEESSSWRDSSRRDDRDRDDRRRERDDRRDLRERRDLRDDRDRRGPPL 1300
1301 RSEREEVSSWRRADDRKDDRVEERDPPRRVPPPALSRDRERDRDREREGE 1350
1351 KEKASWRAEKDRESLRRTKNETDEDGWTTVRR 1382

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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