 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6PDN3 from www.uniprot.org...
The NucPred score for your sequence is 0.58 (see score help below)
1 MGDVKLFASSHMSKTSHSVDPSKVSSMPLTEAPAFILPPRNLCVKEGATA 50
51 KFEGRVRGYPEPQVTWHRKGQAITNGGRFLLDCGVRGTFSLVIHTVREED 100
101 KGKYTCEASNGSGARQVTVELTVEGNSMKKRDQPVLSKASGFPGETRPSI 150
151 WGECPPKFATKLGRAVVKEGQMWRFSCKITGRPPPQVTWLKGNVPLQPSA 200
201 RVSMSEKNGMQILEIRGVTRDDLGVYTCMVVNGSGKASMSAELSIPGLDN 250
251 ASRLAVRGTKAPSPDIRKEVTNGVSKDPETVAESKNCPSPQRSGSSARAT 300
301 NSHLKSPQEPKPKLCEDAPRKVPQSSILQKSTSTITLQALKVQPEARVPA 350
351 IGSFSPGEDRKSLAAPQQATLPTRQSSLGGSVGNKFVTGNIPRESQREST 400
401 FPRFESQPQSQEVTEGQTVKFICEVSGIPKPDVGWFLEGIPVRRREGITE 450
451 VYEDGVSHHLCLLRARTRDSRKYSCTASNSLGQVSCSWSLLVDRPNLAQT 500
501 APSFSSVLKDSVVIEGQDFVLRCSVQGTPAPRVTWLLNGQPIQFAHSICE 550
551 AGVAELHIQDALPEDRGTYTCLAENAMGQVSCSATVTVQEKKGEGEREHR 600
601 LSPARSKPIAPIFLQGLSDLKVMDGSQVTMTVQVSGNPPPEVIWLHDGNE 650
651 IQESEDFHFEQKGGWHSLCIQEVFPEDTGTYTCEAWNSAGEVRTRAVLTV 700
701 QEPHDGTQPWFISKPRSVTATLGQSVLISCAIAGDPFPTVHWLRDGRALS 750
751 KDSGHFELLQNEDVFTLVLKNVQPWHAGQYEILLKNRVGECSCQVSLMLH 800
801 NSPSRAPPRGREPASCEGLCGGGGVGAHGDGDRHGTLRPCWPARGQGWPE 850
851 EEDGEDVRGLLKRRVETRLHTEEAIRQQEVGQLDFRDLLGKKVSTKTVSE 900
901 DDLKDIPAEQMDFRANLQRQVKPKTISEEERKVHSPQQVDFRSVLAKKGT 950
951 PKTPVPEKAPPKAATPDFRSVLGGKKKSPSENGGNSAEVLNVKAGESPTP 1000
1001 AGDAQAIGALKPVGNAKPAETPKPIGNAKPTETLKPVGNTKPAETLKPIA 1050
1051 NAQPSGSLKPVTNAQPAEPQKPVGNAKSAETSKPAGKEEVKEVKNDVNCK 1100
1101 KGQVGATGNEKRPESQGSAPVFKEKLQDVHVAEGEKLLLQCQVISDPPAT 1150
1151 VTWSLNGKTLKTTKFIVLAQEGSRFSVSIEKALPEDRGLYKCVAKNSAGQ 1200
1201 AECSCQVTVDDAQTSENTKAPEMKSRRPKSSLPPVLGTESDATVKKKPAP 1250
1251 KTPTKAAMPPQIIQFPEDQKVRAGEPVELFGKVAGTQPITCKWMKFRKQI 1300
1301 QESEHIKVENGESGSKLTILAARQEHCGCYTLVVENKLGSRQAQVNLTVV 1350
1351 DKPDPPAGTPCASDIRSSSLTLSWYGSSYDGGSAVQSYNVEIWDTEDKVW 1400
1401 KELATCRSTSFNVQDLLPDREYKFRVRAVNVYGTSEPSQESELTAVGEKP 1450
1451 EEPKDEVEVSDDDEKEPEVDYRTVTVNTEQKVSDVYDIEERLGSGKFGQV 1500
1501 FRLVEKKTGKIWAGKFFKAYSAKEKDNIRQEISIMNCLHHPKLVQCVDAF 1550
1551 EEKANIVMVLEIVSGGELFERIIDEDFELTERECIKYMRQISEGVEYIHK 1600
1601 QGIVHLDLKPENIMCVNKTGTRIKLIDFGLARRLENAGSLKVLFGTPEFV 1650
1651 APEVINYEPIGYATDMWSIGVICYILVSGLSPFMGDNDNETLANVTSATW 1700
1701 DFDDEAFDEISDDAKDFISNLLKKDMKNRLDCTQCLQHPWLMKDTKNMEA 1750
1751 KKLSKDRMKKYMARRKWQKTGNAVRAIGRLSSMAMISGLSGRKSSTGSPT 1800
1801 SPINAEKLESEDDVSQAFLEAVAEEKPHVKPYFSKTIRDLEVVEGSAARF 1850
1851 DCKIEGYPDPEVVWFKDDQSIRESRHFQIDYDEDGNCSLIISDVCGDDDA 1900
1901 KYTCKAVNSLGEATCTAELIVETMEEGEGEEGGEEEEEEEE 1941
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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