 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P25384 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MESQQLHQNPRSLHGSAYASVTSKEVPSNQDPLAVSASNLPEFDRDSTKV 50
51 NSQQETTPGTSAVPENHHHVSPQPASVPPPQNGQYQQHGMMTPNKAMASN 100
101 WAHYQQPSMMTCSHYQTSPAYYQPDPHYPLPQYIPPLSTSSPDPIDSQNQ 150
151 HSEVPQAETKVRNNVLPPHTLTSEENFSTWVKFYIRFLKNSNLGDIIPND 200
201 QGEIKRQMTYEEHAYIYNTFQAFAPFHLLPTWVKQILEINYADILTVLCK 250
251 SVSKMQTNNQELKDWIALANLEYDGSTSADTFEITVSTIIQRLKENNINV 300
301 SDRLACQLILKGLSGDFKYLRNQYRTKTNMKLSQLFAEIQLIYDENKIMN 350
351 LNKPSQYKQHSEYKNVSRTSPNTTNTKVTTRNYQRTNSSKPRAAKAHNIA 400
401 TSSKFSRVNNDHINESTVSSQYLSDDNELSLGQQQKESKPTHTIDSNDEL 450
451 PDHLLIDSGASQTLVRSAHYLHHATPNSEINIVDAQKQDIPINAIGNLHF 500
501 NFQNGTKTSIKALHTPNIAYDLLSLSELANQNITACFTRNTLERSDGTVL 550
551 APIVKHGDFYWLSKKYLIPSHISKLTINNVNKSKSVNKYPYPLIHRMLGH 600
601 ANFRSIQKSLKKNAVTYLKESDIEWSNASTYQCPDCLIGKSTKHRHVKGS 650
651 RLKYQESYEPFQYLHTDIFGPVHHLPKSAPSYFISFTDEKTRFQWVYPLH 700
701 DRREESILNVFTSILAFIKNQFNARVLVIQMDRGSEYTNKTLHKFFTNRG 750
751 ITACYTTTADSRAHGVAERLNRTLLNDCRTLLHCSGLPNHLWFSAVEFST 800
801 IIRNSLVSPKNDKSARQHAGLAGLDITTILPFGQPVIVNNHNPDSKIHPR 850
851 GIPGYALHPSRNSYGYIIYLPSLKKTVDTTNYVILQDKQSKLDQFNYDTL 900
901 TFDDDLNRLTAHNQSFIEQNETEQSYDQNTESDHDYQSEIEINSDPLVND 950
951 FSSQSINPLQLDKEPVQKVRAPKEVDADISEYNILPSPVRSRTPHIINKE 1000
1001 STEMGGTVESDTTSPRHSSTFTARNQKRPGSPNDMIDLTSQDRVNYGLEN 1050
1051 IKTTRLGGTEEPYIQRNSDTNIKYRTTNSTPSIDDRSSNSESTTPIISIE 1100
1101 TKAVCDNTPSIDTDPPEYRSSDHATPNIMPDKSSKNVTADSILDDLPLPD 1150
1151 LTHQSPTDTSDVSKDIPHIHSRQTNSSLGGMDDSNVLTTTKSKKRSLEDN 1200
1201 ETEIEVSRDTWNNKNMRSLEPPRSKKRINLIAAIKGVKSIKPVRTTLRYD 1250
1251 EAITYNKDNKEKDRYVEAYHKEISQLLKMNTWDTNKYYDRNDIDPKKVIN 1300
1301 SMFIFNKKRDGTHKARFVARGDIQHPDTYDSDMQSNTVHHYALMTSLSIA 1350
1351 LDNDYYITQLDISSAYLYADIKEELYIRPPPHLGLNDKLLRLRKSLYGLK 1400
1401 QSGANWYETIKSYLINCCDMQEVRGWSCVFKNSQVTICLFVDDMILFSKD 1450
1451 LNANKKIITTLKKQYDTKIINLGESDNEIQYDILGLEIKYQRSKYMKLGM 1500
1501 EKSLTEKLPKLNVPLNPKGKKLRAPGQPGHYIDQDELEIDEDEYKEKVHE 1550
1551 MQKLIGLASYVGYKFRFDLLYYINTLAQHILFPSRQVLDMTYELIQFMWD 1600
1601 TRDKQLIWHKNKPTKPDNKLVAISDASYGNQPYYKSQIGNIFLLNGKVIG 1650
1651 GKSTKASLTCTSTTEAEIHAVSEAIPLLNNLSHLVQELNKKPIIKGLLTD 1700
1701 SRSTISIIKSTNEEKFRNRFFGTKAMRLRDEVSGNNLYVYYIETKKNIAD 1750
1751 VMTKPLPIKTFKLLTNKWIH 1770
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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