 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P47100 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MESQQLSQHSHISHGSACASVTSKEVHTNQDPLDVSASKTEECEKASTKA 50
51 NSQQTTTPASSAVPENPHHASPQTAQSHSPQNGPYPQQCMMTQNQANPSG 100
101 WSFYGHPSMIPYTPYQMSPMYFPPGPQSQFPQYPSSVGTPLSTPSPESGN 150
151 TFTDSSSADSDMTSTKKYVRPPPMLTSPNDFPNWVKTYIKFLQNSNLGGI 200
201 IPTVNGKPVRQITDDELTFLYNTFQIFAPSQFLPTWVKDILSVDYTDIMK 250
251 ILSKSIEKMQSDTQEANDIVTLANLQYNGSTPADAFETKVTNIIDRLNNN 300
301 GIHINNKVACQLIMRGLSGEYKFLRYTRHRHLNMTVAELFLDIHAIYEEQ 350
351 QGSRNSKPNYRRNPSDEKNDSRSYTNTTKPKVIARNPQKTNNSKSKTARA 400
401 HNVSTSNNSPSTDNDSISKSTTEPIQLNNKHDLHLGQKLTESTVNHTNHS 450
451 DDELPGHLLLDSGASRTLIRSAHHIHSASSNPDINVVDAQKRNIPINAIG 500
501 DLQFHFQDNTKTSIKVLHTPNIAYDLLSLNELAAVDITACFTKNVLERSD 550
551 GTVLAPIVKYGDFYWVSKKYLLPSNISVPTINNVHTSESTRKYPYPFIHR 600
601 MLAHANAQTIRYSLKNNTITYFNESDVDWSSAIDYQCPDCLIGKSTKHRH 650
651 IKGSRLKYQNSYEPFQYLHTDIFGPVHNLPKSAPSYFISFTDETTKFRWV 700
701 YPLHDRREDSILDVFTTILAFIKNQFQASVLVIQMDRGSEYTNRTLHKFL 750
751 EKNGITPCYTTTADSRAHGVAERLNRTLLDDCRTQLQCSGLPNHLWFSAI 800
801 EFSTIVRNSLASPKSKKSARQHAGLAGLDISTLLPFGQPVIVNDHNPNSK 850
851 IHPRGIPGYALHPSRNSYGYIIYLPSLKKTVDTTNYVILQGKESRLDQFN 900
901 YDALTFDEDLNRLTASYQSFIASNEIQQSDDLNIESDHDFQSDIELHPEQ 950
951 PRNVLSKAVSPTDSTPPSTHTEDSKRVSKTNIRAPREVDPNISESNILPS 1000
1001 KKRSSTPQISNIESTGSGGMHKLNVPLLAPMSQSNTHESSHASKSKDFRH 1050
1051 SDSYSENETNHTNVPISSTGGTNNKTVPQISDQETEKRIIHRSPSIDASP 1100
1101 PENNSSHNIVPIKTPTTVSEQNTEESIIADLPLPDLPPESPTEFPDPFKE 1150
1151 LPPINSRQTNSSLGGIGDSNAYTTINSKKRSLEDNETEIKVSRDTWNTKN 1200
1201 MRSLEPPRSKKRIHLIAAVKAVKSIKPIRTTLRYDEAITYNKDIKEKEKY 1250
1251 IEAYHKEVNQLLKMKTWDTDEYYDRKEIDPKRVINSMFIFNKKRDGTHKA 1300
1301 RFVARGDIQHPDTYDSGMQSNTVHHYALMTSLSLALDNNYYITQLDISSA 1350
1351 YLYADIKEELYIRPPPHLGMNDKLIRLKKSLYGLKQSGANWYETIKSYLI 1400
1401 QQCGMEEVRGWSCVFKNSQVTICLFVDDMVLFSKNLNSNKRIIEKLKMQY 1450
1451 DTKIINLGESDEEIQYDILGLEIKYQRGKYMKLGMENSLTEKIPKLNVPL 1500
1501 NPKGRKLSAPGQPGLYIDQQELELEEDDYKMKVHEMQKLIGLASYVGYKF 1550
1551 RFDLLYYINTLAQHILFPSKQVLDMTYELIQFIWNTRDKQLIWHKSKPVK 1600
1601 PTNKLVVISDASYGNQPYYKSQIGNIYLLNGKVIGGKSTKASLTCTSTTE 1650
1651 AEIHAISESVPLLNNLSYLIQELDKKPITKGLLTDSKSTISIIISNNEEK 1700
1701 FRNRFFGTKAMRLRDEVSGNHLHVCYIETKKNIADVMTKPLPIKTFKLLT 1750
1751 NKWIH 1755
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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