 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P02567 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MSLEHEKDPGWQYLKRSREQQLADQSRPYDSKKNVWIPDAEEGYIEGVIK 50
51 GPGPKADTVIVTAGGKDVTLKKDIVQEVNPPKFEKTEDMSNLTFLNDASV 100
101 LWNLRSRYAAMLIYTYSGLFCVVINPYKRLPIYTDSVARMFMGKRRTEMP 150
151 PHLFAVSDQAYRYMLQDHENQSMLITGESGAGKTENTKKVICYFATVGAS 200
201 QKAALKEGEKEVTLEDQIVQTNPVLEAFGNAKTVRNNNSSRFGKFIRIHF 250
251 NKHGTLASCDIEHYLLEKSRVIRQAPGERCYHIFYQIYSDFKPQLRDELL 300
301 LNHPISNYWFVAQAELLIDGIDDTEEFQLTDEAFDVLKFSPTEKMDCYRL 350
351 MSAHMHMGNMKFKQRPREEQAEPDGQDEAERACNMYGIDVDQFLKALVSP 400
401 RVKVGTEWVSKGQNVDQVHWAIGAMAKGLYARVFHWLVKKCNLTLDQKGI 450
451 DRDYFIGVLDIAGFEIFDFNSFEQLWINFVNEKLQQFFNHHMFVLEQEEY 500
501 AREGIQWTFIDFGLDLQACIELIEKPLGIISMLDEECIVPKATDMTLAQK 550
551 LTDQHLGKHPNFEKPKPPKGKQGEAHFAMRHYAGTVRYNVLNWLEKNKDP 600
601 LNDTVVSVMKASKKNDLLVEIWQDYTTQEEAAAAAKAGGGRKGGKSGSFM 650
651 TVSMMYRESLNKLMTMLHKTHPHFIRCIIPNEKKQSGMIDAALVLNQLTC 700
701 NGVLEGIRICRKGFPNRTQHPDFVQRYAILAAKEAKSSDDMKTCAGAILQ 750
751 ALINQKQLNDEQFRIGHTKVFFKAGVVAHIEDLRDDKLNQIITGFQSAIR 800
801 WYTATADAGARRKQLNSYIILQRNIRSWCVLRTWDWFLLFGKLRPQLKCG 850
851 KMAEEMIKMAEEQKVLEAEAKKAESARKSQEEAYAKLSAERSKLLEALEL 900
901 TQGGSAAIEEKLTRLNSARQEVEKSLNDANDRLSEHEEKNADLEKQRRKA 950
951 QQEVENLKKSIEAVDGNLAKSLEEKAAKENQIHSLQDEMNSQDETIGKIN 1000
1001 KEKKLLEENNRQLVDDLQAEEAKQAQANRLRGKLEQTLDEMEEAVEREKR 1050
1051 IRAETEKSKRKVEGELKGAQETIDELSAIKLETDASLKKKEADIHALGVR 1100
1101 IEDEQALANRLTRQSKENAQRIIEIEDELEHERQSRSKADRARAELQREL 1150
1151 DELNERLDEQNKQLEIQQDNNKKKDSEIIKFRRDLDEKNMANEDQMAMIR 1200
1201 RKNNDQISALTNTLDALQKSKAKIEKEKGVLQKELDDINAQVDQETKSRV 1250
1251 EQERLAKQYEIQVAELQQKVDEQSRQIGEYTSTKGRLSNDNSDLARQVEE 1300
1301 LEIHLATINRAKTAFSSQLVEAKKAAEDELHERQEFHAACKNLEHELDQC 1350
1351 HELLEEQINGKDDIQRQLSRINSEISQWKARYEGEGLVGSEELEELKRKQ 1400
1401 MNRVMDLQEALSAAQNKVISLEKAKGKLLAETEDARSDVDRHLTVIASLE 1450
1451 KKQRAFDKIVDDWKRKVDDIQKEIDATTRDSRNTSTEVFKLRSSMDNLSE 1500
1501 QIETLRRENKIFSQEIRDINEQITQGGRTYQEVHKSVRRLEQEKDELQHA 1550
1551 LDEAEAALEAEESKVLRLQIEVQQIRSEIEKRIQEKEEEFENTRKNHQRA 1600
1601 LESIQASLETEAKSKAELARAKKKLETDINQLEIALDHANKANVDAQKNL 1650
1651 KKLFDQVKELQGQVDDEQRRREEIRENYLAAEKRLAIALSESEDLAHRIE 1700
1701 ASDKHKKQLEIEQAELKSSNTELIGNNAALSAMKRKVENEVQIARNELDE 1750
1751 YLNELKASEERARKAAADADRLAEEVRQEQEHAVHVDRQRKSLELNAKEL 1800
1801 QAKIDDAERAMIQFGAKALAKVEDRVRSLEAELHSEQRRHQESIKGYTKQ 1850
1851 ERRARELQFQVEEDKKAFDRLQENVEKLQQKIRVQKRQIEEAEEVATQNL 1900
1901 SKFRQIQLALENAEERAEVAENSLVRMRGQVVRSATNK 1938
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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