 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5VZ89 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MIEDKGPRVTDYFVVAGLTDTSTLLDQEINRLDTKSTGPKAPITDIAIII 50
51 KSAGETVPEGYTCVEATPSALQANLNYGSLKSPELFLCYKRGRDKPPLTD 100
101 IGVLYEGKERLIPGCEVILATPYGRCANVNNSSTTSQRIFITYRRAPPVR 150
151 PQNSLAVTDICVIVTSKGETPPHTFCKVDKNLNCGMWGSSVFLCYKKSVP 200
201 ASNAIAYKAGLIFRYPEEDYESFPLSESDVPLFCLPMGATIECWDPETKY 250
251 PLPVFSTFVLTGSSAKKVYGAAIQFYEPYSRELLSEKQLMHLGLLTPVER 300
301 KMVSKSINTNKCICLLSHWPFFEAFRKFLMFIYKLSVSGPHPLPIEKHIS 350
351 HFMQNIPFPSPQRPRILVQLSVHDALILSQPVSTPLPLSGANFSTLLMNL 400
401 GPENCATLLLFVLLESKILLHSLRPAVLTGVAEAVVAMIFPFQWQCPYIP 450
451 LCPLSLAAVLSAPLPFIVGVDSRYFDLHDPPQDVVCIDLDTNMLYVSDEK 500
501 KNMNWKQLPKKPCKNLLSTLKKLYPQLSSVHQKTQEGSAIDMTPIEADFS 550
551 WQKKMTQLEMEIQEAFLRFMASILKGYRTYLRPITEAPSNKATAADSLFD 600
601 RQGFLKSRDRAYAKFYTLLSKTQIFIRFIEECSFVSDKDTGLAFFDDCIE 650
651 KLFPDKGTEKTDKVDFDSAEDTRLIELDDSQKSEHTVFIMPPEPPPDDGK 700
701 DLSPKYSYKYFPRLDLKLFDRPQELKLCFSRHPTGNSITKSPPLMAKRTK 750
751 QEIKTAHKLAKRCYTNPPQWAKCLFSHCYSLWFICLPAYVRVSHPKVRAL 800
801 QQAYDVLIKMRKTDVDPLDEVCYRVVMQLCGLWGHPVLAVRVLFEMKTAR 850
851 IKPNAITYGYYNKVVLESPWPSSTRSGIFLWTKVRNVVRGLAQFRQPLKK 900
901 TVQRSQVSSISGGQSDQGYGSKDELIKDDAEIHVPEEQAARELITKTKMQ 950
951 TEEVCDASAIVAKHSQPSPEPHSPTEPPAWGSSIVKVPSGIFDVNSRKSS 1000
1001 TGSISNVLFSTQDPVEDAVFGEATNLKKNGDRGEKRQKHFPERSCSFSSE 1050
1051 SRAGMLLKKSSLDSNSSEMAIMMGADAKILTAALTCPKTSLLHIARTHSF 1100
1101 ENVSCHLPDSRTCMSESTWNPEHRSSPVPEMLEESQELLEPVVDDVPKTT 1150
1151 ATVDTYESLLSDSNSNQSRDLKTVSKDLRNKRSSLYGIAKVVQREDVETG 1200
1201 LDPLSLLATECTGGKTPDSEDKLFSPVIARNLADEIESYMNLKSPLGSKS 1250
1251 SSMELHREENRESGMTTAFIHALERRSSLPLDHGSPAQENPESEKSSPAV 1300
1301 SRSKTFTGRFKQQTPSRTHKERSTSLSALVRSSPHGSLGSVVNSLSGLKL 1350
1351 DNILSGPKIDVLKSGMKQAATVASKMWVAVASAYSYSDDEEETNRDYSFP 1400
1401 AGLEDHILGENISPNTSISGLVPSELTQSNTSLGSSSSSGDVGKLHYPTG 1450
1451 EVPFPRGMKGQDFEKSDHGSSQNTSMSSIYQNCAMEVLMSSCSQCRACGA 1500
1501 LVYDEEIMAGWTADDSNLNTACPFCKSNFLPLLNIEFKDLRGSASFFLKP 1550
1551 STSGDSLQSGSIPLANESLEHKPVSSLAEPDLINFMDFPKHNQIITEETG 1600
1601 SAVEPSDEIKRASGDVQTMKISSVPNSLSKRNVSLTRSHSVGGPLQNIDF 1650
1651 TQRPFHGISTVSLPNSLQEVVDPLGKRPNPPPVSVPYLSPLVLRKELESL 1700
1701 LENEGDQVIHTSSFINQHPIIFWNLVWYFRRLDLPSNLPGLILTSEHCNE 1750
1751 GVQLPLSSLSQDSKLVYIQLLWDNINLHQEPREPLYVSWRNFNSEKKSSL 1800
1801 LSEEQQETSTLVETIRQSIQHNNVLKPINLLSQQMKPGMKRQRSLYREIL 1850
1851 FLSLVSLGRENIDIEAFDNEYGIAYNSLSSEILERLQKIDAPPSASVEWC 1900
1901 RKCFGAPLI 1909
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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