 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9P6L5 from www.uniprot.org...
The NucPred score for your sequence is 0.87 (see score help below)
1 MSSFRLQSDHMQSDASLMTSVRKATSIDETAPKRKHVRSCIIFTWDHHTA 50
51 RPFWTAIKVQPLLANEVQTFKALITIHRVLQEGHKSALVDSQSEKGWLKT 100
101 CERQYDGESSPKGYSDLIRDYVDYLLDKLSFHAQHPEFNGTFEYKEYISL 150
151 RQVDDPNEGYETVYDMMNLQDHIDEFQKQLFSNFKRSNKNECRIAALVPL 200
201 VQESYGIYRFLTSMLRALYSTVDAPETLEPLKHRYKSQHHRLRQFYADCS 250
251 NLRYLTSLISVPRLPHDPPDLEGDDNIPDLPKRPASIAPQPTGASTIAPQ 300
301 PTGTSPSPPVEMNFPDTSDITPAYSEPEPIQDFWSDPTLDQQLAAQQAAQ 350
351 QAAQQQAELAAQQAAAQQAQLAAQQAAEMERQRMAAQQHQQALEAIQMAQ 400
401 AEQQRIAQEQLAQQQFQMQTQGQLAELEQQLLATRGQLEQSNVLLNQYDA 450
451 RVRTLENELSQAGVNLQEQIHQNDDLIESLKNQILTWKNKYEALAKLYTQ 500
501 LRQEHLDLLSKYKQIQLKASSAQEAIDKKEKMEREMKNKNLELADMILER 550
551 DRARHELETMHRSQRDKQESTERELRLLQEKAASLERNKSSEVSNLLSRY 600
601 NTEVAHLEDALHSKDRELANLGVELKSTENRYRQLLQEKEEELEIQKAAV 650
651 DESLLQLSKLQLDRNDIDQAMDTQIDELLKSQLEKLDDIVDSVLATGIQR 700
701 LDTSLYELDSPMHAGNQYATPEFILSTIENASNNATDFSTAFNNYFADGP 750
751 NADHSEVINGVNLFSTAIYEVANNAKGLSRTTGDDQGSDRFVGLSRDLVN 800
801 MAKRFLSSLFSVNTRKMDVNVKTDLVIGENIELQRYLQQLTQYSEKFLNK 850
851 ESENTVGLLNAPGENIEELVDNQLAETAQAIQQAILRLQNIAAKPKDDSL 900
901 SPSELQVHDSLLSASIAITEAIARLIKAATASQAEIVAQGRGSSSRGAFY 950
951 KKHNRWTEGLISAAKAVARATTTLIETADGVVNGTSSFEHLIVACNGVSA 1000
1001 ATAQLVAASRVKANFASKVQDHLEDAAKAVTEACKALVRQVESVALKAKE 1050
1051 VQHEDFSSLGVHEYRRKEIEQQVQILKLENDLVAARRRLFDMRKTSYHVA 1100
1101 EE 1102
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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