 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6BTX0 from www.uniprot.org...
The NucPred score for your sequence is 0.83 (see score help below)
1 MSPQWMPQNIQKRLLLYVLQQLSLFSEIDLPNLEEVSLNNIVLKNVSIDP 50
51 DKVGKLPGCNLRYGQVGSLELNGGVMGGVSIDANNVEIVIAPDFDMKEEI 100
101 SNNVQFSLAQSTADLANTLMVDKSSNEYESSDDETDTVMPSVSSKSRSNS 150
151 SSSGTSARTRPSALSGVMTKAVEMALSRLQVKVTNLNIKIVSESTDLVLK 200
201 VDEALLNTINGTRHVKIKGVKLITLKPEVNPGESSDDSPEQESPKESENS 250
251 NTSDDDEDNDNDYGDESLMNSMVFTHDEASSIYMSATSQSFNKPSNNDDT 300
301 APTETAPDNKESPILLHIDDIDIEFEGLSNITNLEIDVGEIKVAAVPITP 350
351 TIISIFNNISHNLKLKYYQQRKSNIHKQRFKSNLSFPQYADDNDEIEDEN 400
401 EQMPILDDNGASSGPFFDKLRIHNIIVSATSALLPTGQFASASNSLNFIF 450
451 HNLNIKYKNEALIYGGIEVFKIVKITNDQEIEVLKFNNSTAPTNTEPNPS 500
501 DEPAGSTSAPSNSSKADIRFEAFTKLDNEIKHLEFTSLFSKQAFVNLDKS 550
551 VLLLLSNFGISVSSIYDSYNTMRSTMNSVNSFKANTNINGEPRDASSIGV 600
601 AKESNLQIILQTASTTINIKLSDNLNLKAVIYPISFNLLKQGMSINKILI 650
651 STVSSGIETLISTLSNIQLSTKSQEFKSFSNKSGYSKGSNDSFPRETILG 700
701 SNLTLSLSKISSKASLKELKLLIGDFADFASSWQLLSLQVNSLKNSVKDK 750
751 GFVMSSKSNKNESSSMLSNSMYFNQRRSRRSNFNNPSLVNTNRSNLVSFR 800
801 LYVDHIEFCITNVLPKLGDFDFQLEKVSFYKLNNDIQGSIHTVKVDRNLG 850
851 NGEAVNDFIYEFQRKRCNKINIPLILVNIKSNDKANTIDISLRNFLIEYY 900
901 TRWLELLEKEIDENAVLHDITGQKRESSSLNSPSKRLDIRFSLYDCVIGL 950
951 NPGRLDCKSLLIINKGNSDVTFGLHQFYIKSSLRNLSLLIIDDVKNINLS 1000
1001 KTDREAASKPTSTAYISPLSWFTSIGYISVGNINCIHLGITVNTGIQEII 1050
1051 ERNEKLGLQDNLALLDIKINSDEHQLDLCADSAHVLIQMINDLKPPLSFT 1100
1101 DEEKIKVTVNDPINLLDEIGQNVFLNESIMKSASHSETFENSTISRKNSD 1150
1151 ANDINIVEEYYDGSHTSSQSLENGFNKLSISESDNAKDDASSFSFDEEHF 1200
1201 SSNGADRNNTEVFPIKMNINLSKTKIYLYDGFDWKGTRKTIKGAVKRVEA 1250
1251 QALQELERVKEHGSRKHLKRNMQVTFDEPESNATEDNYGNDQENDDGNSS 1300
1301 DNQSLIGETLFQSIHLSVPKGSNPSSLTKNINKSVQNYFDNEDSNDSSIN 1350
1351 YNVETGRNYKNLKLRRSKNHKISIDLKNIEVNMAILTTRDPRRDKDVPDV 1400
1401 KYEVTNSIDLRIEDIDIYDNIPNSTWNKFLSYMNSLGEREIGTSMLKASI 1450
1451 TNVRPNPELCSTEAMIDISILPIRLHVDQDALDFFIRFFDFKDKRFELPI 1500
1501 DEIIYIQMFKMSSIKLKLDYKPKKIDYSGIRSGKVSEFVNFFILDGSELS 1550
1551 LPKLTLYGILGMPMLGAELTKTWAPNIQQTQLSGLLAGLSPFRSIVNIGG 1600
1601 GFKDLVAVPIKEYRKDGRLMRSLQKGTSKFAKTTGYELLNLGAKLASGTQ 1650
1651 VVLEQSEQVFGGEGSSARSPKNKNDKHGKIEDDDNEDIYTSGNTSKGNSN 1700
1701 LLASSQLLNKTIAVDNDPYGKKKLYSYIELDESDDIDDKILENSLLLMNP 1750
1751 KDIKESRQLQVVSEESELQELDEKEELDDEDAIKLVSLYSNQPENTQQGL 1800
1801 KLAYKSLGENFEITKKAVNNLRKELNASSNVQESLKSMVKSSPILIIRPM 1850
1851 IGTTEALSKALMGISNEIDSNHIIESKDKYRYDASEK 1887
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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