 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8WML3 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MVKLANPLYTEWILEAIQKIKKQKQRPSEERICHAVSTSHGLDKKTVSEQ 50
51 LELSVQDGSVLKVTNKGLASYKDPDNPGRFSSVKPGTFPKSTKESRGSCN 100
101 DLRNVDWNKLLRRAIEGLEEPNGSSLKNIEKYLRSQSDLTSTTNNPAFQQ 150
151 RLRLGAKRAVNNGRLLKDGPQYRVNYGSLDGKGAPQYPSAFPSSLPPVSL 200
201 LPHEKDQPRADPIPICSFCLGTKESNREKKPEELLSCADCGSSGHPSCLK 250
251 FCPELTTNVKALRWQCIECKTCSACRVQGRNADNMLFCDSCDRGFHMECC 300
301 DPPLSRMPKGMWICQVCRPKKKGRKLLHEKAAQIKRRYAKPIGRPKNKLK 350
351 QRLLSVTSDEGSMNAFTGRGSPDTEIKINIKQESADVNVIGNKDVVTEED 400
401 LDVFKQAQELSWEKIECESGVEDCGRYPSVIEFGKYEIQTWYSSPYPQEY 450
451 ARLPKLYLCEFCLKYMKSKNILLRHSKKCGWFHPPANEIYRRKDLSVFEV 500
501 DGNMSKIYCQNLCLLAKLFLDHKTLYYDVEPFLFYVLTKNDEKGCHLVGY 550
551 FSKEKLCQQKYNVSCIMIMPQHQRQGFGRFLIDFSYLLSRREGQAGSPEK 600
601 PLSDLGRLSYLAYWKSVILEYLYHHHERHISIKAISRATGMCPHDIATTL 650
651 QHLHMIDKRDGGFVIIRREKLILSHMEKLKTCSRANELDPDSLRWTPILI 700
701 SNAAVSEEEREAEKEAERLMEQASCWEKEEQEVLSTRANSRQSPAKVQSK 750
751 NKYLHSPESRPVTGERGQLLELSKESSEEEEEEEEDEEEEDEEEEEEEEE 800
801 DEEEEEEEEEEEEEEEEENIQSSPPRLTKPQSVAIKRKRPFVLKKKRGRK 850
851 RRRINSSVTTETISETTEVLNEPFDNSDEERPMPQLEPTCEIEVEEDGRK 900
901 PVLRKAFQHQPGKKRQTEEEEGKDNHCFKNADPCRNNMNDDSRNLKEGSK 950
951 DNPEPLKCKQAWPKGTKRGLSKWRQNKERKTGFKLNLYTPPETPLEPDEQ 1000
1001 VTVEEQKETSEGKTSPTPISIEEEAKEAGEALLPQEENRRQETCAPVSPN 1050
1051 TSPGEKPEDDLIKPEEEEEEEEEEEEEEGEEEEEEGGNVEKDPDGAKSQE 1100
1101 KEEPEISPEKEDSARLDDHEEEEEEDEEPSHNEDHDADDEDDSHMESAEV 1150
1151 EKEELPRESFKEVLENEEAFLDLNVQPSHSNPEVLMDCGVDLTASCNSEP 1200
1201 KELAGDPEAVPESDEEPPPGEQAQKQDQKNSKEVDTEFKEGNPATMEIDS 1250
1251 ETVQAVQSLTQESSEQDDTFQDCAETQEACRSLQNYTRADQSPQIATTLD 1300
1301 DCQQSDHSSPVSSVHSHPGQSVRSVNSPSVPALENSYAQISPDQSAISVP 1350
1351 SLQNMETSPMMDVPSVSDHSQQVVDSGFSDLGSIESTTENYENPSSYDST 1400
1401 MGGSICGNGSSQNSCSYSNLTSSSLTQSSCAVTQQMSNISGSCSMLQQTS 1450
1451 ISSPPTCSVKSPQGCVVERPPSSSQQLAQCSMAANFTPPMQLAEIPETGN 1500
1501 ANIGLYERMGQSDFGAGHYPQPSATFSLAKLQQLTNTLIDHSLPYSHSAA 1550
1551 VTSYANSASLSTPLSNTGLVQLSQSPHSVPGGPQAQATMTPPPNLTPPPM 1600
1601 NLPPPLLQRNMAASNIGISHSQRLQTQIASKGHVSMRTKSASLSPAAATH 1650
1651 QSQIYGRSQTVAMQGPARTLTMQRGMNMSVNLMPAPAYNVNSVNMNMNTL 1700
1701 NAMNGYSMSQPMMNSGYHSNHGYMNQTPQYPMQMQMGMMGTQPYAQQPMQ 1750
1751 TPPHGNMMYTAPGHHGYMNTGMSKQSLNGSYMRR 1784
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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