 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P40989 from www.uniprot.org...
The NucPred score for your sequence is 0.65 (see score help below)
1 MSYNDPNLNGQYYSNGDGTGDGNYPTYQVTQDQSAYDEYGQPIYTQNQLD 50
51 DGYYDPNEQYVDGTQFPQGQDPSQDQGPYNNDASYYNQPPNMMNPSSQDG 100
101 ENFSDFSSYGPPSGTYPNDQYTPSQMSYPDQDGSSGASTPYGNGVVNGNG 150
151 QYYDPNAIEMALPNDPYPAWTADPQSPLPIEQIEDIFIDLTNKFGFQRDS 200
201 MRNMFDHFMTLLDSRSSRMSPEQALLSLHADYIGGDTANYKKWYFAAQLD 250
251 MDDEIGFRNMKLGKLSRKARKAKKKNKKAMQEASPEDTEETLNQIEGDNS 300
301 LEAADFRWKSKMNQLSPFEMVRQIALFLLCWGEANQVRFTPECLCFIYKC 350
351 ASDYLDSAQCQQRPDPLPEGDFLNRVITPLYRFIRSQVYEIVDGRYVKSE 400
401 KDHNKVIGYDDVNQLFWYPEGIAKIVMEDGTRLIDLPAEERYLKLGEIPW 450
451 DDVFFKTYKETRSWLHLVTNFNRIWIMHISVYWMYCAYNAPTFYTHNYQQ 500
501 LVDNQPLAAYKWATAALGGTVASLIQVAATLCEWSFVPRKWAGAQHLSRR 550
551 FWFLCVIMGINLGPVIFVFAYDKDTVYSTAAHVVGAVMFFVAVATLVFFS 600
601 VMPLGGLFTSYMKKSTRSYVASQTFTASFAPLHGLDRWMSYLVWVTVFAA 650
651 KYAESYFFLILSLRDPIRILSTTSMRCTGEYWWGNKICKVQPKIVLGLMI 700
701 ATDFILFFLDTYLWYIVVNTVFSVGKSFYLGISILTPWRNIFTRLPKRIY 750
751 SKILATTDMEIKYKPKVLISQIWNAIIISMYREHLLAIDHVQKLLYHQVP 800
801 SEIEGKRTLRAPTFFVSQDDNNFETEFFPRDSEAERRISFFAQSLSTPIP 850
851 EPLPVDNMPTFTVLTPHYAERILLSLREIIREDDQFSRVTLLEYLKQLHP 900
901 VEWDCFVKDTKILAEETAAYENNEDEPEKEDALKSQIDDLPFYCIGFKSA 950
951 APEYTLRTRIWASLRSQTLYRTISGFMNYSRAIKLLYRVENPEIVQMFGG 1000
1001 NADGLERELEKMARRKFKFLVSMQRLAKFKPHELENAEFLLRAYPDLQIA 1050
1051 YLDEEPPLNEGEEPRIYSALIDGHCEILENGRRRPKFRVQLSGNPILGDG 1100
1101 KSDNQNHALIFYRGEYIQLIDANQDNYLEECLKIRSVLAEFEELGIEQIH 1150
1151 PYTPGLKYEDQSTNHPVAIVGAREYIFSENSGVLGDVAAGKEQTFGTLFA 1200
1201 RTLAQIGGKLHYGHPDFINATFMTTRGGVSKAQKGLHLNEDIYAGMNAVL 1250
1251 RGGRIKHCEYYQCGKGRDLGFGTILNFTTKIGAGMGEQMLSREYYYLGTQ 1300
1301 LPIDRFLTFYYAHPGFHLNNLFIQLSLQMFMLTLVNLHALAHESILCVYD 1350
1351 RDKPITDVLYPIGCYNFHPAIDWVRRYTLSIFIVFWIAFVPIVVQELIER 1400
1401 GLWKATQRFFRHILSLSPMFEVFAGQIYSSALLSDIAVGGARYISTGRGF 1450
1451 ATSRIPFSILYSRFAGSAIYMGSRSMLMLLFGTVAHWQAPLLWFWASLSA 1500
1501 LIFAPFIFNPHQFAWEDFFLDYRDYIRWLSRGNNKYHRNSWIGYVRMSRS 1550
1551 RVTGFKRKLVGDESEKSAGDASRAHRTNLIMAEIIPCAIYAAGCFIAFTF 1600
1601 INAQTGVKTTDEDRVNSTLRIIICTLAPIVIDIGVLFFCMGLSCCSGPLL 1650
1651 GMCCKKTGSVMAGIAHGIAVVVHIVFFIVMWVLEGFSFVRMLIGVVTCIQ 1700
1701 CQRLIFHCMTVLLLTREFKNDHANTAFWTGKWYSTGLGYMAWTQPTRELT 1750
1751 AKVIELSEFAADFVLGHVILIFQLPVICIPKIDKFHSIMLFWLKPSRQIR 1800
1801 PPIYSLKQARLRKRMVRRYCSLYFLVLIIFAGCIVGPAVASAHVPKDLGS 1850
1851 GLTGTFHNLVQPRNVSNNDTGSQMSTYKSHYYTHTPSLKTWSTIK 1895
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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