 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q01529 from www.uniprot.org...
The NucPred score for your sequence is 0.58 (see score help below)
1 MKKNNTILYYGCAAQARYASSNHGLLYSPSQAHLFNFSLARTYLNFSNGF 50
51 RAFSSERKRQNSWKLSVRSIYMDSVNFTKHDFINALLKNFKQGNVYTVLV 100
101 KVEYLDSSGNRAWCMLNVQKGIIYRNKSDFIELVKEFFDEVYIGYIEYMS 150
151 RYHAQEVLSIQIMYILNNDSYRQYSLKNINKEKLDKNLVNVKQTKLDFSE 200
201 SLLPLTTNEKFYGKRLTPILDYKKQFVTSLYINGINFIKLVNKKSKDLNQ 250
251 EFINFDSKTRFYRYKLNEIEYIITVSNISKTETVKTIYLMTGFKFKDNIL 300
301 DKELTTKIFSRQIGNTTIEFDGADIINKEIKLKLPIIRLNYKPFTDLNSR 350
351 IGTFDLETFRDYNSNSAVYALGFSTLSMSKTDKKTSMYYLTKDGNTSHEI 400
401 IIKCINEMLSSDYRDHIYFTHNLGGYDIIFILHALKLENKIILENKLKGI 450
451 NTIVEDDKKIKVKKKKPISDVNKKSQNKDHYEISTILRDDRILKCVIKVK 500
501 TPSGYNKITFIDSYNILPDKLDNLAKSFGTEIQKGLFPYEFVKSNTLNYV 550
551 GITPSIEYYKINNEVISQELYNELIVPQWDLRKQTLHYLERDLLSLLEII 600
601 NTYNHYVYKRYNVQLTESLTIARLALNIYLKRYLGDNLIPVVLNNSLFTS 650
651 IKAAYYGGVAEVYRPYGKNLRYYDVNSLYPFVAKNTMPGHECKYIESKKG 700
701 LKLSELFGFFYCKVTTNNQYLGLLPVHNQGLIMPNGQWYGWYFSEELKFA 750
751 EVNGYNIEVIKGYQFNKIDNLFSSYVDDLYKIKANSEGSEKLITKFLLNS 800
801 LLGRFGMSIFKLKTDIVSVEKAKKLAVTNYINSVKAISDTDVLISYNKEI 850
851 SRKLVEEHGLNYIEILNSNSKLDLEKNNSFKDVAVSISAAVTAYARIFMA 900
901 QTKLDILKNGGNLYYTDTDSIVTDIDLPDNLVGSELGQFKLEFKLKEGFF 950
951 ISAKTYCLILEKEYIKKNKNKDTVIKAKGVFKTSLDVEKFKSLYFNKQDV 1000
1001 EAIKSNNKTNYLEGYVNIESGIVKLKHDAYTKRSKIYDNNGLWIDTKPLN 1050
1051 YQVSNMLEDTNSKPLNSPNNNDLCALIKYNKPCFDLIKYNKSITDLILYL 1100
1101 PTNKAKFINYAQLESMINEAIHESDMRVANHIKMLIYSLTGILYHGKDGT 1150
1151 MYIYSPNSKKIYIKYKKNNKWVTFWNIKYHNGYVYIKNKNKFYLYKG 1197
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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