 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P34333 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MESFKELAREYDEKFKAFQDDLQKWEETSERKEYAEFHRVQAESEFPELK 50
51 REREDRERWARAERIRGEDEKSMLAKEHADKKIRLGVAKIPRLLTESERK 100
101 MDEFVERPGSILKDMKKEHRQSVLDRLEEWSPEERSLFKSRQADHVKIFH 150
151 GLTEFFVDKTASDLVLFYYMNKKTEDYKKDFKPKKRVTKYKVGAFPSVEE 200
201 LAYFRMMPPLDFSSFPKNSLMCYFCCRTVNGIDLNGTFMPKEAYEIFAIC 250
251 PDEDRVVCSGCREEAAKLYKDNRCFGNRCSNQKKRANRVNRNIPLDFADF 300
301 PVRTRAFIMDKLGSTRVAVKFCTPCKNALTRWINDVNNKEETIMAELLNY 350
351 EGQVGWTDDEKTKLVTLINSSPTLDWVSISEGMNRRPNECKMQYDAMNGV 400
401 KTQPMIEEVDEEDGNGQEEGGDALVNTPTTSSAAARRSGLARNAKKPVRT 450
451 PRAPRSAGGRRTGGAVTRAQAVPKPVEDLGEEIDEMEIEDNDEDASRGSR 500
501 GKDSKAPSDRDGSPADMEGDSPEGQDQDADQDQDQDQDVDEEEEEVIVRD 550
551 IDSPVKTLLSPKILSGGHKPDFPPVPRIQKPSTSSQPPPPEPMDTKENES 600
601 DDGEEDNDILEIDVDEPPAKRPTPTSSSSHLIGSSSVGGSERELGGRGLV 650
651 QQQQQQQPQAQSAAPPVTVSTAAAATAERLVNATSPSPSVASQHLVPTET 700
701 STSVPPVTIVPPAIQQPVVVISGAAPQFTQQQTTHSPALIAQPIPQQLIP 750
751 QRVSTPAQILTPTPVRPTAASTPSMDQFLGLFKQQQQQQQQQPQQSNLMQ 800
801 QLGNINPQFLALLLQQQQQQQQVQQAQVQAAQTQGSLTSGTPFQAQQRPD 850
851 EALQKLFSSPEMLGTLLNAKYQFPQFPQAIQQNPLLMNAQHQLILQQQQL 900
901 AMQHAQAQAAQAAQAQAAQAAQAQAQAQAEAKLKTQAAQAKAQADAQARV 950
951 QTQQQAHLKAQAQAQYQMNRPQLIPASVQMPIGINTAYHQKSLTPSETSA 1000
1001 SATPPAHRPRAATTVGSKMPAGRSNVQEAELRTLKEELIKRIRLFRDRIA 1050
1051 EDAHLKREEENIVTYTAQIQASRVQYNTEILGQMKQRYEQAAARRIEIVK 1100
1101 ELDEPAKFINGVQNKFNDFSVFKLDEIDRQTLHEILQRYAAEQKPDQLQQ 1150
1151 QQNDFHNLLRQNNIGIRQAQYPALQASPHQAAIIQHQQQQEAFKKLQQQH 1200
1201 QDAQKRKLEAPVSSATPQVKRIALSQSSPVQRFSQHPNGTLPHNLAVVYQ 1250
1251 NKMPQDREKLLQEQQLNQYLFAAQQQHLQQQQQHHGTQPEQKSKRKSGIE 1300
1301 SITSMQGAPHRHIQLAGPSSSRIQSGRGVSPALSASRSVAPTISGAAGRS 1350
1351 ITAGTSGHSSTSDYNKELAERMNEVFKPTHPQLLQTKASAMNSNAVSPAN 1400
1401 TNNSDEIECVYQGPPKTPASIKRLQPTEGPRTLSGQRMKSILSVPAHQRR 1450
1451 SSIPPVKTEDEAMECLSMMMYEEAKAPPSDRIVTKLISSSEAAAAANPSA 1500
1501 KFSYLDIFNDVVKRDEERCQRMLQSTSVLQPSRELDAFLQQLQQNPQQYA 1550
1551 NLSAAEKLALQQYQIHSAHQKSQQQAQLQAAQQLQQQQQARPDHYEKFHL 1600
1601 LRPNAEIVRPIPTTFSHFLNKATTSTVSSSASAPQFLQPPAAASIAAPTP 1650
1651 ISTPHAMPSPSVGVQTAPPTPQAVHHPVMPIIPGKPSSVNSNVSDVSSDD 1700
1701 DDVRNPEKLPANRLPPLPGDKTAFRSVIDLRATGHVAVTKKIPVKYPLVV 1750
1751 QAQNGIQPIKDYGPPCKNLVYEDLSDDE 1778
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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