 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O75096 from www.uniprot.org...
The NucPred score for your sequence is 0.62 (see score help below)
1 MRRQWGALLLGALLCAHGLASSPECACGRSHFTCAVSALGECTCIPAQWQ 50
51 CDGDNDCGDHSDEDGCILPTCSPLDFHCDNGKCIRRSWVCDGDNDCEDDS 100
101 DEQDCPPRECEEDEFPCQNGYCIRSLWHCDGDNDCGDNSDEQCDMRKCSD 150
151 KEFRCSDGSCIAEHWYCDGDTDCKDGSDEENCPSAVPAPPCNLEEFQCAY 200
201 GRCILDIYHCDGDDDCGDWSDESDCSSHQPCRSGEFMCDSGLCINAGWRC 250
251 DGDADCDDQSDERNCTTSMCTAEQFRCHSGRCVRLSWRCDGEDDCADNSD 300
301 EENCENTGSPQCALDQFLCWNGRCIGQRKLCNGVNDCGDNSDESPQQNCR 350
351 PRTGEENCNVNNGGCAQKCQMVRGAVQCTCHTGYRLTEDGHTCQDVNECA 400
401 EEGYCSQGCTNSEGAFQCWCETGYELRPDRRSCKALGPEPVLLFANRIDI 450
451 RQVLPHRSEYTLLLNNLENAIALDFHHRRELVFWSDVTLDRILRANLNGS 500
501 NVEEVVSTGLESPGGLAVDWVHDKLYWTDSGTSRIEVANLDGAHRKVLLW 550
551 QNLEKPRAIALHPMEGTIYWTDWGNTPRIEASSMDGSGRRIIADTHLFWP 600
601 NGLTIDYAGRRMYWVDAKHHVIERANLDGSHRKAVISQGLPHPFAITVFE 650
651 DSLYWTDWHTKSINSANKFTGKNQEIIRNKLHFPMDIHTLHPQRQPAGKN 700
701 RCGDNNGGCTHLCLPSGQNYTCACPTGFRKISSHACAQSLDKFLLFARRM 750
751 DIRRISFDTEDLSDDVIPLADVRSAVALDWDSRDDHVYWTDVSTDTISRA 800
801 KWDGTGQEVVVDTSLESPAGLAIDWVTNKLYWTDAGTDRIEVANTDGSMR 850
851 TVLIWENLDRPRDIVVEPMGGYMYWTDWGASPKIERAGMDASGRQVIISS 900
901 NLTWPNGLAIDYGSQRLYWADAGMKTIEFAGLDGSKRKVLIGSQLPHPFG 950
951 LTLYGERIYWTDWQTKSIQSADRLTGLDRETLQENLENLMDIHVFHRRRP 1000
1001 PVSTPCAMENGGCSHLCLRSPNPSGFSCTCPTGINLLSDGKTCSPGMNSF 1050
1051 LIFARRIDIRMVSLDIPYFADVVVPINITMKNTIAIGVDPQEGKVYWSDS 1100
1101 TLHRISRANLDGSQHEDIITTGLQTTDGLAVDAIGRKVYWTDTGTNRIEV 1150
1151 GNLDGSMRKVLVWQNLDSPRAIVLYHEMGFMYWTDWGENAKLERSGMDGS 1200
1201 DRAVLINNNLGWPNGLTVDKASSQLLWADAHTERIEAADLNGANRHTLVS 1250
1251 PVQHPYGLTLLDSYIYWTDWQTRSIHRADKGTGSNVILVRSNLPGLMDMQ 1300
1301 AVDRAQPLGFNKCGSRNGGCSHLCLPRPSGFSCACPTGIQLKGDGKTCDP 1350
1351 SPETYLLFSSRGSIRRISLDTSDHTDVHVPVPELNNVISLDYDSVDGKVY 1400
1401 YTDVFLDVIRRADLNGSNMETVIGRGLKTTDGLAVDWVARNLYWTDTGRN 1450
1451 TIEASRLDGSCRKVLINNSLDEPRAIAVFPRKGYLFWTDWGHIAKIERAN 1500
1501 LDGSERKVLINTDLGWPNGLTLDYDTRRIYWVDAHLDRIESADLNGKLRQ 1550
1551 VLVSHVSHPFALTQQDRWIYWTDWQTKSIQRVDKYSGRNKETVLANVEGL 1600
1601 MDIIVVSPQRQTGTNACGVNNGGCTHLCFARASDFVCACPDEPDSRPCSL 1650
1651 VPGLVPPAPRATGMSEKSPVLPNTPPTTLYSSTTRTRTSLEEVEGRCSER 1700
1701 DARLGLCARSNDAVPAAPGEGLHISYAIGGLLSILLILVVIAALMLYRHK 1750
1751 KSKFTDPGMGNLTYSNPSYRTSTQEVKIEAIPKPAMYNQLCYKKEGGPDH 1800
1801 NYTKEKIKIVEGICLLSGDDAEWDDLKQLRSSRGGLLRDHVCMKTDTVSI 1850
1851 QASSGSLDDTETEQLLQEEQSECSSVHTAATPERRGSLPDTGWKHERKLS 1900
1901 SESQV 1905
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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