 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5JCS6 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MSDPRPSQAEKHKLGRAASKFKDPSRAMQSDDYFARKFKAINGSMGPATL 50
51 NTSSLSEGGGGGGGPANGTPAVPKMGVRARVSEWPPKKDCSKDLACKTLW 100
101 ESRSQSSYESATSIIQNGQNDQVDRQQEEQLDLDFVEAKYTIGDIFVHSP 150
151 QRGLHPIRQRSNSDITISDIDTEDVLDQHAVNPNTGAALHREYGSTSSID 200
201 RQGLSGENVFAMLRGYRIESYDPKVTSSFGFPDFFPCDTAISPSLHAAAQ 250
251 ISRGEFVRISGLDYMDGGLLMGRDRDKPFKRRLKSESVETSLFRKLRTVK 300
301 SEHETFKFTSDLEEGRLDRGIRPWSCQRCFAHYDVQSILFNINEAMATRA 350
351 SVGKRKNITTGASAASQTPVPVGPAGGCESPLGSKEDLNAKENPDADEGD 400
401 GKSNDLVLSCPYFRNETGGEGDRRIALSRANSASFSSGESCSFESSLSSH 450
451 CTNAGVSVLEVPRENQPIHREKVKRYIIEHVDLGAYYYRKFFYGKEHQNY 500
501 FGIDENLGPVAVSIRREKVEDPREKEGSQFNYRVAFRTSELTTLRGAILE 550
551 DAVPSTARHGTARGLPLKEVLEYVIPELSIPCLRQAANSPKVPEQLLKLD 600
601 EQGLSFQHKIGILYCKAGQSTEEEMYNNETAGPAFEEFLDLLGQRVRLKG 650
651 FSKYRAQLDNKTDSTGTHSLYTTYKDFELMFHVSTLLPYMPNNRQQLLRK 700
701 RHIGNDIVTIVFQEPGALPFTPKNIRSHFQHVFVIVKVHNPCTENVCYSV 750
751 GVFRSKDVPPFVPPIPKGVTFPRTGVFRDFLLAKGINAENAAHKSEKFRA 800
801 MATRTRHEYLKDLAENFVTTTTVDTSAKFSFITLGAKKKERVKPRTDAHL 850
851 FSIGAIMWHVVARYFGQSADIECLLGISNEFIMLIEKESKNVAFNCSCRD 900
901 VIGWTSGLVSIKIFYERGECILLSSVDNSSEDIREIVQRLVIVTRGCETV 950
951 EMTLRRNGLGQLGFHVNFEGIVADVEPFGFAWKAGLRQGSRLVEICKVAV 1000
1001 ATLTHEQMIDLLRTSVTVKVVIIQPHEDGSPRRGCSELCRIPMVEYKLDS 1050
1051 EGTPCEYKTPFRRNTTWHRVPTPALQPVSRASPVPGTPDRLQCQPLLQQA 1100
1101 QAAIPRSTSFDRKLPDGTRSSPSNQSSSSDPGPGGSGPWRPQVGYDGCPS 1150
1151 PLLLEPQGPGSVECDGSGDHEDLMEVGRLPETKWHGPPSKVLSSYKERAL 1200
1201 QKDGSCKDSPNKLSHIGDKSCSSHSSSNTLSSNTSSNSDDKHFGSGDLMD 1250
1251 PELLGLTYIKGASTDSGIDTTPCMPATILGPMHLTGSRSLIHSRAEQWAD 1300
1301 AADVSGADEDPAKMYTLHGYASAISSSAADGSMGDLSEVSSHSSGSHRSG 1350
1351 SPSTHCSKSTGSLDSSKVYIVTHSGGQQVPGAVAKPYHRQGAANKYVIGW 1400
1401 KKSEGSPPPEEPEVTECPRIYGEMDIMSTASQHPAVVGDSVPEAQHVLSK 1450
1451 DDFLKLMLPDSPLVEEGRRKFSFYGNLSPRRSLYRTLSDESVCSNRRGSS 1500
1501 FASSRSSILDQALPNDILFSTTPPYHSTLPPRTHPAPSMGSLRNEFWFSD 1550
1551 GSLSDKSKCADPGLMPLPDTAAGLDWSHLVDAARAFEGLDSDEELGLLCH 1600
1601 HASYLDQRVASFCTLTDLQHGQELEGAPELSLCVDPTSGKEFMDTPGERS 1650
1651 PSTLTGKVNQLELILRQLQTDLRKEKQDKAVLQAEVQHLRQDNMRLQEES 1700
1701 QTATAQLRTFTEWFFSTIDKKV 1722
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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