| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P78312 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MKVRLLRQLSAAAKVKAPSGLQGPPQAHQFISLLLEEYGALCQAARSIST 50
51 FLGTLENEHLKKFQVTWELHNKHLFENLVFSEPLLQSNLPALVSQIRLGT 100
101 TTHDTCSEDTYSTLLQRYQRSEEELRRVAEEWLECQKRIDAYVDEQMTMK 150
151 TKQRMLTEDWELFKQRRFIEEQLTNKKAVTGENNFTDTMRHMLSSRLSMP 200
201 DCPNCNYRRRCACDDCSLSHILTCGIMDPPVTDDIHIHQLPLQVDPAPDY 250
251 LAERSPPSVSSASSGSGSSSPITIQQHPRLILTDSGSAPTFCSDDEDVAP 300
301 LSAKFADIYPLSNYDDTEVVANMNGIHSELNGGGENMALKDESPQISSTS 350
351 SSSSEADDEEADGESSGEPPGAPKEDGVLGSRSPRTEESKADSPPPSYPT 400
401 QQAEQAPNTCECHVCKQEASGLTPSAMTAGALPPGHQFLSPEKPTHPALH 450
451 LYPHIHGHVPLHTVPHLPRPLIHPTLYATPPFTHSKALPPAPVQNHTNKH 500
501 QVFNASLQDHIYPSCFGNTPEWNSSKFISLWGSEVMNDKNWNPGTFLPDT 550
551 ISGSEILGPTLSETRPEALPPPSSNETPAVSDSKEKKNAAKKKCLYNFQD 600
601 AFMEANKVVMATSSATSSVSCTATTVQSSNSQFRVSSKRPPSVGDVFHGI 650
651 SKEDHRHSAPAAPRNSPTGLAPLPALSPAALSPAALSPASTPHLANLAAP 700
701 SFPKTATTTPGFVDTRKSFCPAPLPPATDGSISAPPSVCSDPDCEGHRCE 750
751 NGVYDPQQDDGDESADEDSCSEHSSSTSTSTNQKEGKYCDCCYCEFFGHG 800
801 GPPAAPTSRNYAEMREKLRLRLTKRKEEQPKKMDQISERESVVDHRRVED 850
851 LLQFINSSETKPVSSTRAAKRARHKQRKLEEKARLEAEARAREHLHLQEE 900
901 QRRREEEEDEEEEEDRFKEEFQRLQELQKLRAVKKKKKERPSKDCPKLDM 950
951 LTRNFQAATESVPNSGNIHNGSLEQTEEPETSSHSPSRHMNHSEPRPGLG 1000
1001 ADGDAADPVDTRDSKFLLPKEVNGKQHEPLSFFFDIMQHHKEGNGKQKLR 1050
1051 QTSKASSEPARRPTEPPKATEGQSKPRAQTESKAKVVDLMSITEQKREER 1100
1101 KVNSNNNNKKQLNHIKDEKSNPTPMEPTSPGEHQQNSKLVLAESPQPKGK 1150
1151 NKKNKKKKGDRVNNSIDGVSLLLPSLGYNGAILAHCNLRLPGSSDCAASA 1200
1201 SQVVGITDDVFLPKDIDLDSVDMDETEREVEYFKRFCLDSARQTRQRLSI 1250
1251 NWSNFSLKKATFAAH 1265
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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