 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P09849 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MELFWSIVFTVLLSFSCRGSDWESDSNFISAAGPLTTDLLLSLQYPQGNQ 50
51 TSDFAAGGKDLYVCSQPLPAFLPEYFSSLRASEITHYKVFLSWAQLLPAG 100
101 HSGDPDGNAVRCYRQLLEALRAAQLQPMVVLHHQHLPASSALRSAVFADL 150
151 FAEYATFAFHAFGDLVGVWLTFSDLEAAIRELPQPESRASRLQLLTEAHR 200
201 KAYEIYHQKYAAQGGKVSVVLQAEEISELLLESSTSALAKDSIDFLSLDL 250
251 SYECQSEMSLPEKLSKLQTIEPKVKVFIFTLRLQDCPSSRKSPASLLFSF 300
301 IEAINKDQVLTLGFDVNAFLNCSSTSKKSISCFLTDSLALQTDHERAARN 350
351 SAPVSTYQRVWEMFAHQPRAERDAFLQDTFPQGFLWGVSTGAFNVEGGWA 400
401 EGGRGPSVWDQFGHLKAAQGQATPEVASDSYYKWASDVALLRGLRAQVYK 450
451 FSISWSRIFPMGRGSSPSPQGVAYYNKLIDSLLDSHIEPMATLFHWDLPQ 500
501 ALQDEGGWQNESVVDAFVDYAAFCFSAFGNRVKLWVTFHEPWVMSYAGYG 550
551 TGQHAPGISDPGIASFQVAHLVLKAHARTWHHYNSHHRPQQQGRVGIVLN 600
601 SDWAEPLSPERPEDLAASERFLHFMLGWFAHPIFVDGDYPATMKAQIQQR 650
651 NEQCPSPVAQLPEFTDTEKQLLKGSADFLGLSHYTSRLISKAPEDSCIPS 700
701 YDTIGGFSQHTDPAWPQTSSPWIRVVPWGIRRLLQFVSLEYTKGKVPIYL 750
751 AGNGMPIGESENLLSDSLRVDYFNQYINEVLKAIKEDSVDVRSYIARSLM 800
801 DGFEGPAGYSQRFGLYHVNFNESSKPRTPRKSAFLLTSIIEKNGFLTKAV 850
851 KQPLPPNSAHLPSKTRASALPSEVPSKAKVVWEKFSNQTKFERDLFYHGT 900
901 FRDDFLWGVSSSAYQIEGAWDADGKGPSIWDNFTHTPGNGVTDNSTGDIA 950
951 CDSYNQLDADLNVLRALKVKAYRFSLSWSRIFPTGTNSSINSHGVDYYNR 1000
1001 LIDGLLASDIFPMVTLFHWDLPQALQDIGGWENPSLIDLFDSYADYCFQT 1050
1051 FGDRVKFWITFNEPTYYSWWSYGSGTFPPNVNDPGWAPYRISHALIKAHA 1100
1101 RVYHTYDEKYRQSQNGVISLSLVAQWAEPKSPDVLRDVEAADRKMQFTLG 1150
1151 WYAHPIFKTGDYPDAMKWKVGNRSELQHLATSRLPSFTEEEKSYIRGTAD 1200
1201 VFCLNTYSSKIVQHKTPALNPPSYEDDQELAEEEDTSWPTTAMNRAASFG 1250
1251 MRRLLNWIKEEYGDIPIYITENGVGLTNPRLEDIDRIFYYKTYINEALKA 1300
1301 YRLDGVNLRGYFAWSLMDNFEWLQGYTIKFGLYHVDFENVNRPRTARISA 1350
1351 SYYTELITNNGMPLPSEDEFVYGQFPEGFVWSTSTAAFQIEGAWRADGKG 1400
1401 LGIWDTFTHTRLKIENDDIADVACDSYHKISEDVVALQNLAVTHYRFSIS 1450
1451 WSRILPDGTTNYINEAGLNYYVRLIDALLAANIKPQVTMYHFDLPQALQD 1500
1501 VGGWENETIVQRFKEYADVLFQRLGDKVKFWITLNEPFVVAYHGYGTGLY 1550
1551 APGIYFRPGTAPYIVGHNLIKAHAEAWHLYNDVYRASQGGVISITISSDW 1600
1601 AEPRDPSNQEDVEAAKRYVQFMGGWFAHPIFKNGDYNEVMKTQIRERSLA 1650
1651 AGLNESRLPEFTESEKRRINGTYDFFGFNHYTTVLAYNFNYPSIMSTVDA 1700
1701 DRGVASIVDRSWPGSGSYWLKMTPFGFRRILNWIKEEYNNPPIYVTENGV 1750
1751 SHRGDSYLNDTTRIYYLRSYINEALKAVQQDKVDLRGYTVWTLMDNFEWY 1800
1801 TGFSDKFGLHFVNYSDPSLPRIPRESAKFYASIVRCNGFPDPAEGPHPCL 1850
1851 LQPEDTDPTMSPVSQEEVQFLGLSLGSTEAETALYVLFSLMLLGVCGLAF 1900
1901 LSYALCKSSKQRKKLSQQELSPVSSF 1926
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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