 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P28494 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MKLSRQFTVFGSAIFCVVIFSLYLMLDRGHLDYPRGPRQEGSFPQGQLSI 50
51 LQEKIDHLERLLAENNEIISNIRDSVINLSESVEDGPRGPAGNASQGSAH 100
101 LHSAQLALQADPKDCLFASQSGNQHRDVQMLDVYDLIPFDNPDGGVWKQG 150
151 FDIKYEADEWDREPLQVFVVPHSHNDPGWLKTFNDYFRDKTQYIFNNMVL 200
201 KLKEDSSRKFIWSEISYLAKWWDIIDNPKKEAVKSLLQNGQLEIVTGGWV 250
251 MADEATTHYFALIDQLIEGHQWLEKNLGVKPRSGWAIDPFGHSPTMTYLL 300
301 KRAGFSHMLIQRVHYSVKKHFSLQKTLEFFWRQNWDLGSTTDILCHMMPF 350
351 YSYDIPHTCGPDPKICCQFDFKRLPGGRYGCPWGVPPEAISPGNVQSRAQ 400
401 MLLDQYRKKSKLFRTKVLLAPLGDDFRFSEYTEWDLQYRNYEQLFSYMNS 450
451 QPHLKVKIQFGTLSDYFDALEKSVAAEKKGGQSVFPALSGDFFTYADRDD 500
501 HYWSGYFTSRPFYKRMDRIMESRLRTAEILYHLALKQAQKYKINKFLSSP 550
551 HYTTLTEARRNLGLFQHHDAITGTAKDWVVVDYGTRLFQSLNSLEKIIGD 600
601 SAFLLILKDKKLYQSDPSKAFLEMDTKQSSQDSLPKKNIIQLSAQEPRYL 650
651 VVYNPFEQERHSVVSVRVNSATVKVLSDLGKAVEVQVSAVWKDMRTTSQA 700
701 AYEVAFLAHLPPLGLKVYKILESQSSSSHLADYFLYNNDGQAESGIFHMK 750
751 NMVDSGDAITIENSFLTLGFDRSGLMEKVRRKEDNKQQELKVQFLWYGTT 800
801 NKRDKSGAYLFLPDGQGQPYVSLRTPFVRVTRGRIYSDVTCFLEHVTHKV 850
851 RLYHIQGIEGQSMEVSNIVDIRSVHNREIVMRISSKINNQNRYYTDLNGY 900
901 QIQPRRTMAKLPLQANVYPMSTMAYIQDAAHRLTLLSAQSLGASSMASGQ 950
951 IEVFMDRRLMQDDNRGLGQGVHDNKITANLFRILLEKRNGMNMEEDKKSP 1000
1001 VSYPSLLSHMTSAFLNHPFLPMVLSGQLPSPAIELLSEFRLLQSSLPCDI 1050
1051 HLVNLRTIQSKVGKGYSDEAALILHRKVFDCQLSSRAMGLPCSTTQGKMS 1100
1101 IPKLFNNFAVESFIPSSLSLMHSPPDAQNTSEVSLSPMEISTSRIRLR 1148
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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