 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P51805 from www.uniprot.org...
The NucPred score for your sequence is 0.66 (see score help below)
1 MPSVCLLLLLFLAVGGALGNRPFRAFVVTDTTLTHLAVHRVTGEVFVGAV 50
51 NRVFKLAPNLTELRAHVTGPVEDNARCYPPPSMRVCAHRLAPVDNINKLL 100
101 LIDYAARRLVACGSIWQGICQFLRLDDLFKLGEPHHRKEHYLSGAQEPDS 150
151 MAGVIVEQGQGPSKLFVGTAVDGKSEYFPTLSSRKLISDEDSADMFSLVY 200
201 QDEFVSSQIKIPSDTLSLYPAFDIYYIYGFVSASFVYFLTLQLDTQQTLL 250
251 DTAGEKFFTSKIVRMCAGDSEFYSYVEFPIGCSWRGVEYRLVQSAHLAKP 300
301 GLLLAQALGVPADEDVLFTIFSQGQKNRASPPRQTILCLFTLSNINAHIR 350
351 RRIQSCYRGEGTLALPWLLNKELPCINTPMQINGNFCGLVLNQPLGGLHV 400
401 IEGLPLLADSTDGMASVAAYTYRQHSVVFIGTRSGSLKKVRVDGFQDAHL 450
451 YETVPVVDGSPILRDLLFSPDHRHIYLLSEKQVSQLPVETCEQYQSCAAC 500
501 LGSGDPHCGWCVLRHRCCREGACLGASAPHGFAEELSKCVQVRVRPNNVS 550
551 VTSPGVQLTVTLHNVPDLSAGVSCAFEAAAENEAVLLPSGELLCPSPSLQ 600
601 ELRALTRGHGATRTVRLQLLSKETGVRFAGADFVFYNCSVLQSCMSCVGS 650
651 PYPCHWCKYRHTCTSRPHECSFQEGRVHSPEGCPEILPSGDLLIPVGVMQ 700
701 PLTLRAKNLPQPQSGQKNYECVVRVQGRQQRVPAVRFNSSSVQCQNASYS 750
751 YEGDEHGDTELDFSVVWDGDFPIDKPPSFRALLYKCWAQRPSCGLCLKAD 800
801 PRFNCGWCISEHRCQLRTHCPAPKTNWMHLSQKGTRCSHPRITQIHPLVG 850
851 PKEGGTRVTIVGENLGLLSREVGLRVAGVRCNSIPAEYISAERIVCEMEE 900
901 SLVPSPPPGPVELCVGDCSADFRTQSEQVYSFVTPTFDQVSPSRGPASGG 950
951 TRLTISGSSLDAGSRVTVTVRDSECQFVRRDAKAIVCISPLSTLGPSQAP 1000
1001 ITLAIDRANISSPGLIYTYTQDPTVTRLEPTWSIINGSTAITVSGTHLLT 1050
1051 VQEPRVRAKYRGIETTNTCQVINDTAMLCKAPGIFLGRPQPRAQGEHPDE 1100
1101 FGFLLDHVQTARSLNRSSFTYYPDPSFEPLGPSGVLDVKPGSHVVLKGKN 1150
1151 LIPAAAGSSRLNYTVLIGGQPCSLTVSDTQLLCDSPSQTGRQPVMVLVGG 1200
1201 LEFWLGTLHISAERALTLPAMMGLAAGGGLLLLAITAVLVAYKRKTQDAD 1250
1251 RTLKRLQLQMDNLESRVALECKEAFAELQTDINELTNHMDEVQIPFLDYR 1300
1301 TYAVRVLFPGIEAHPVLKELDTPPNVEKALRLFGQLLHSRAFVLTFIHTL 1350
1351 EAQSSFSMRDRGTVASLTMVALQSRLDYATGLLKQLLADLIEKNLESKNH 1400
1401 PKLLLRRTESVAEKMLTNWFTFLLHKFLKECAGEPLFLLYCAIKQQMEKG 1450
1451 PIDAITGEARYSLSEDKLIRQQIDYKTLTLHCVCPENEGSAQVPVKVLNC 1500
1501 DSITQAKDKLLDTVYKGIPYSQRPKAEDMDLEWRQGRMTRIILQDEDVTT 1550
1551 KIECDWKRLNSLAHYQVTDGSLVALVPKQVSAYNMANSFTFTRSLSRYES 1600
1601 LLRTASSPDSLRSRAPMITPDQETGTKLWHLVKNHDHADHREGDRGSKMV 1650
1651 SEIYLTRLLATKGTLQKFVDDLFETVFSTAHRGSALPLAIKYMFDFLDEQ 1700
1701 ADQRQISDPDVRHTWKSNCLPLRFWVNVIKNPQFVFDIHKNSITDACLSV 1750
1751 VAQTFMDSCSTSEHRLGKDSPSNKLLYAKDIPNYKSWVERYYRDIAKMAS 1800
1801 ISDQDMDAYLVEQSRLHASDFSVLSALNELYFYVTKYRQEILTALDRDAS 1850
1851 CRKHKLRQKLEQIISLVSSDS 1871
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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