 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Y238 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 METRSSKTRRSLASRTNECQGTMWAPTSPPAGSSSPSQPTWKSSLYSSLA 50
51 YSEAFHYSFAARPRRLTQLALAQRPEPQLLRLRPSSLRTQDISHLLTGVF 100
101 RNLYSAEVIGDEVSASLIKARGSENERHEEFVDQLQQIRELYKQRLDEFE 150
151 MLERHITQAQARAIAENERVMSQAGVQDLESLVRLPPVKSVSRWCIDSEL 200
201 LRKHHLISPEDYYTDTVPFHSAPKGISLPGCSKLTFSCEKRSVQKKELNK 250
251 KLEDSCRKKLAEFEDELDHTVDSLTWNLTPKAKERTREPLKKASQPRNKN 300
301 WMNHLRVPQRELDRLLLARMESRNHFLKNPRFFPPNTRYGGKSLVFPPKK 350
351 PAPIGEFQSTEPEQSCADTPVFLAKPPIGFFTDYEIGPVYEMVIALQNTT 400
401 TTSRYLRVLPPSTPYFALGLGMFPGKGGMVAPGMTCQYIVQFFPDCLGDF 450
451 DDFILVETQSAHTLLIPLQARRPPPVLTLSPVLDCGYCLIGGVKMTRFIC 500
501 KNVGFSVGRFCIMPKTSWPPLSFKAIATVGFVEQPPFGILPSVFELAPGH 550
551 AILVEVLFSPKSLGKAEQTFIIMCDNCQIKELVTIGIGQLIALDLIYISG 600
601 EKSQPDPGELTDLTAQHFIRFEPENLRSTARKQLIIRNATHVELAFYWQI 650
651 MKPNLQPLMPGETFSMDSIKCYPDKETAFSIMPRKGVLSPHTDHEFILSF 700
701 SPHELRDFHSVLQMVLEEVPEPVSSEAESLGHSSYSVDDVIVLEIEVKGS 750
751 VEPFQVLLEPYALIIPGENYIGINVKKAFKMWNNSKSPIRYLWGKISDCH 800
801 IIEVEPGTGVIEPSEVGDFELNFTGGVPGPTSQDLLCEIEDSPSPVVLHI 850
851 EAVFKGPALIINVSALQFGLLRLGQKATNSIQIRNVSQLPATWRMKESPV 900
901 SLQERPEDVSPFDIEPSSGQLHSLGECRVDITLEALHCQHLETVLELEVE 950
951 NGAWSYLPVYAEVQKPHVYLQSSQVEVRNLYLGVPTKTTITLINGTLLPT 1000
1001 QFHWGKLLGHQAEFCMVTVSPKHGLLGPSEECQLKLELTAHTQEELTHLA 1050
1051 LPCHVSGMKKPLVLGISGKPQGLQVAITISKESSDCSTEQWPGHPKELRL 1100
1101 DFGSAVPLRTRVTRQLILTNRSPIRTRFSLKFEYFGSPQNSLSKKTSLPN 1150
1151 MPPALLKTVRMQEHLAKREQLDFMESMLSHGKGAAFFPHFSQGMLGPYQQ 1200
1201 LCIDITGCANMWGEYWDNLICTVGDLLPEVIPVHMAAVGCPISSLRTTSY 1250
1251 TIDQAQKEPAMRFGTQVSGGDTVTRTLRLNNSSPCDIRLDWETYVPEDKE 1300
1301 DRLVELLVFYGPPFPLRDQAGNELVCPDTPEGGCLLWSPGPSSSSEFSHE 1350
1351 TDSSVEGSSSASNRVAQKLISVILQAHEGVPSGHLYCISPKQVVVPAGGS 1400
1401 STIYISFTPMVLSPEILHKVECTGYALGFMSLDSKVEREIPGKRHRLQDF 1450
1451 AVGPLKLDLHSYVRPAQLSVELDYGGSMEFQCQASDLIPEQPCSGVLSEL 1500
1501 VTTHHLKLTNTTEIPHYFRLMVSRPFSVSQDGASQDHRAPGPGQKQECEE 1550
1551 ETASADKQLVLQAQENMLVNVSFSLSLELLSYQKLPADQTLPGVDIQQSA 1600
1601 SGEREMVFTQNLLLEYTNQTTQVVPLRAVVAVPELQLSTSWVDFGTCFVS 1650
1651 QQRVREVYLMNLSGCRSYWTMLMGQQEPAKAAVAFRVSPNSGLLEARSAN 1700
1701 APPTSIALQVFFTARSSELYESTMVVEGVLGEKSCTLRLRGQGSYDERYM 1750
1751 LPHQP 1755
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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