 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q4P328 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MSPGDSALDYAKRQAGNVSSQAPSRPSSENDANGTVSTSNEHPSNEAGPS 50
51 RPRSMGSERSASPQQGTTPKVPTKRRRLNAELAFSSPGPAFQVEQHGSEA 100
101 QSDSNDSSGRARRPRRSTTLTKSGSNESQDRRSSAHIPKRKEEAGESRNL 150
151 AESVPKNKLKLNNGKARASDEVELRESSLSLVLPSRSRSRSKSVVKLEPD 200
201 QDSAFPQEVATPTLQPTRPKPQITPLTALNPQAALSEILARRRSERIALA 250
251 QSDLEDVHDGHDMLVRELFHLTKFVTMVGYDPDVARTDQSDVFTTFKHAH 300
301 DLRFSLDDSGSGAEASTAARVTRRRVNARLESLSLKRPDPPSTPSTPSFS 350
351 KVKVDDDKKSAPEGRRNRRFSSVTGAQPRVNGAHTLETGHSDDTDDSSEE 400
401 EDSEGSDLDAYSPDGREKGDAKDYNASRKGDAKRARLSSTPHKRHRAKVQ 450
451 DASSNAPVKRTGPRKSKALDELDAFILRQQPRPLPDHPPPLHILAPHQIP 500
501 AHRRFGGDLDALYESFNMLQDDEGGLEDDDLETYIKLDQRWRAGLPIHPE 550
551 AGSTTRHAVQKVPRNKSHHDHLLESVTSSYSQMRQYAKLKQQNSRKVARM 600
601 IAQHWERQLGTSEREKKAEERRLRALAKWTLREVLKQWRLAVNVVRARKA 650
651 AAEKAEKEKSDKEQLNAILEQSTAMLKKQHEVMTRADSLDDSDDEGSDRT 700
701 NYGSDGSAESEISDIDDDDNQLIQIQDELPSVSPEQSLDMLTPVPEEADG 750
751 SKDRVSNTTDHEAATANGDPTVVVESESQPSRRPQRRTARTKTFKARDSK 800
801 LDADDIEFNDAGNDDEQEDAELERQMLEEDEEDDSEDAGLAADANIPIEE 850
851 LLKRYGYGQEADQDAEDSDAGEDAVSNDDSLENSATKDGSEDVAAVASIK 900
901 IQEDAEVEEERPVQEDSMPDEAMDLEDDAVSTALNRPSDALLVDDHSDAE 950
951 SAATSGRRSSRRSMTRASSIVSSDRHATRLRQPFLLRGQLRPYQQIGFEW 1000
1001 LCSLYANGVNGILADEMGLGKTIQTISLLAHLACDKGVWGPHLVVAPTSV 1050
1051 MLNWEVEFKKFLPGFKILSYYGNQKERKEKRIGWNTENSFNVCITSYQLV 1100
1101 LADQHIFRRKPWVYLVLDEAHHIKNFRSQRWQTLLGFNSQRRLLLTGTPL 1150
1151 QNNLMDLWSLMYFLMPNGATELPGGGAFANMKDFQDWFSNPLDKAIEGGT 1200
1201 SMNDETRAMVQKLHAVLRPYLLRRLKSEVEKELPSKYEHVITCRLSKRQR 1250
1251 FLYNDFMSRAKTRESLASGNYLSIINCLMQLRKVCNHPDLFEVRPIVTSF 1300
1301 AMSRSVVADYEIKDLLVRRRLLQENVWEKVDLDVTNLRITDGEEHLTAIE 1350
1351 SRDLRRLNAAKKLPHFREAVPEPRELDTWTLEGFERSREQRKLVDRMEKW 1400
1401 KHMAYLNQYRCTKRPIYGSGLIKMLTEAGEAARLEPLEQHESDRRGFLTR 1450
1451 CDSVLRIVQSRSTRRENMQALIDRFAFVTPRAVAVDMPRWALPGLEAHQR 1500
1501 PDMVKREFDTVHPVAVKLHIAFPDASLLQYDCGKLQQLDILMRRLKEGGH 1550
1551 RILIFTQMTRVLDILESFLNYHGYRYLRLDGATKVESRQALTEQFNRDAR 1600
1601 ISAFILSTRSGGLGINLTGADTVLFYDLDWNAAIEAQCMDRAHRIGQTRD 1650
1651 VHIYRFVTEHTIEENMLRKANQKRLLDNVVIQQGEFNTETLAKRLDWTDM 1700
1701 LDESGKIGDVEVVVADQGVGARDVESAFLQAEDDEDRQAALRARHEMFID 1750
1751 DADFEEHQPSTSRPNTASATPLAHTASDGARPDNGAHAADALDAHEIENE 1800
1801 HQEQEQEQEQAASIDDYMLAFVESDWPFFA 1830
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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