 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P54683 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MKFQFSSPSKIFLFSSVILILIFIGIKFELLEDTNSNRNDKFNNIINRFI 50
51 NYNIDDSIYKNKQQQQQFSNKIYSNEKKILLKNKIIDTTIKPSININNNN 100
101 NNNNKLNNNNNNNNNNNNNNNNNNNNNNNNNNNNYYNSIEYYSSFVSRLL 150
151 KSNDDDGIYYDDYQSKYKKNHYIVQFKDRINDETREQLKEFLIGTDITIL 200
201 KEQPFKSHIVHYIPHDSFLVFMTKEQSVLLSSKEWISWIGEHEPSNKIHL 250
251 NYHEKSIGYPVYIILSGSTNSLIQRWENTLNSILTSYNSKVKLTLINQKK 300
301 LKSIVYCNDESPSSSSSSSCSLIGSEKIVYKWISEQSESNYIERSEKLQT 350
351 ANRLSPTVIFGTKDKLVNNDRIDIPLRGKGQILSIADTGLDGSHCFFSDS 400
401 KYPIPFNQVNENHRKVVTYITYHDNEDYVNGHGTHVCGSAAGTPEDSSWA 450
451 ISSFSGLATDAKIAFYDLSSGSSEPTPPEDYSQMYKPLYDAGARVHGDSW 500
501 GSVSLQGYYGGYSDDAGGIDAFLYEYPEFSILRAAGNNELFASLLAQATA 550
551 KNAITVGAEQTAHVNYVSDALEYYDFSDNANFQRPCLFDKKYCNYTTAKC 600
601 CSEVSNVKGLQLCCPASIKQNASDSFTTQPQFYNENNMGSFSSKGPTHDG 650
651 RLKPDIVAPGEYITSARSNGENSTDQCGDGSLPNANGLMSISGTSMATPL 700
701 ATAATTILRQYLVDGYFPTGESVEENKLLPTGSLLKALMINNAQLLNGTY 750
751 FWSASSTNPSNAIFEQINGANLIQGWGALRMNNWLYVKSSNPTPPSRWIG 800
801 IGGLGKNQKATEWKEDSLSSGLNKSYCFTYKPSSSSSGSGGGGGTPRIVA 850
851 TLVWTDPPSYSGAKFNLVNNLDLLLLNSDDDSIITIGNSGGSLQPAGKVA 900
901 QPDTLNNVEGIIINPTKAMNYKFTIAGTNVPIGPQKFSFVFHGENGQFDW 950
951 ADSCPQCVDGVQFPCLITNGIGIQSCGSDLLWTKCIVQSCNEGYNYNSLK 1000
1001 NTCDKFLSYNYIIIIVAGGTMVLIILLLMWIKYQEYKESKRDSFRRFDDG 1050
1051 TGIFVRPKDKDAKVTPPDLYNLVSPFIIELTIATACSLVATAASILQPFY 1100
1101 IGNIVNNIPTTKSIGEFKSDFIIIFILAFIEFLFTNVGSWISGIVNEKMV 1150
1151 MRLQNKVFRALIAQDMGFFQRNNSALLMNVLIVDTPMLRSALTGILLSIA 1200
1201 TGVCKLVGSLVFIFTISWKLSLAFFAAVPILGLVTQIQSQFTKRLTRQLL 1250
1251 FHNSKASQHGTESLTNMHVVTNYCKQEKEMVKYSDQLMNVFITARKLIIT 1300
1301 NTFAGTGKWLLIESLTFVILYFSAYLVIQKQFTVGLMISFSLYIGYVVDA 1350
1351 SSSLFGVYVSYIQCLASATRVFMILRSAPRKRTTLEEEEADRLAGLSGGG 1400
1401 GGGGDNGDDKKDKQNIENGKDVLPSNIITPIDNVENSNGKQDDPNNNNNN 1450
1451 IGNLDYSEQLDGVSTVADSTVGLTKRELKKQKEKEQKEYFKQTGISVAET 1500
1501 PTFLPSSYTELTECRGEIEFKNVSFRYPTRPDVQVLHNINMKFEAGKCYG 1550
1551 LVGPSGSGKSTTLELISKFYPLHGETGGKIYMDGIDIAKIRPNNLRSFVT 1600
1601 NVHQHPFLFDATIGENIGYAIDNPTQEDIIEAAKLAYAHEFINDLPKKYD 1650
1651 TQIGEAGNLSGGQKKRIAVARAICAKRKIMLLDEITAELDPESEEAITQS 1700
1701 IKVLTQGHTVVMVAHKVAAVRDCDKIFVLEKGYLVEEGTHDELMANKGKY 1750
1751 YRMFSEDKDDTPLQNNNNNKNNNNNNNNNEPSSSSTPPNDQPTPPPQEQQ 1800
1801 EQKNDQPPPPPPQEQQEQQEQQQQQQQEQQQQQQQQQQQQQQQQQQQQQQ 1850
1851 QQQQQQQQQQQNDQPPNDYDQVPPPPPLPSESPSPPTGNNDGQPLVQMDE 1900
1901 ENDEER 1906
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.) |
Go back to the NucPred Home Page.