 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q14185 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MTRWVPTKREEKYGVAFYNYDARGADELSLQIGDTVHILETYEGWYRGYT 50
51 LRKKSKKGIFPASYIHLKEAIVEGKGQHETVIPGDLPLIQEVTTTLREWS 100
101 TIWRQLYVQDNREMFRSVRHMIYDLIEWRSQILSGTLPQDELKELKKKVT 150
151 AKIDYGNRILDLDLVVRDEDGNILDPELTSTISLFRAHEIASKQVEERLQ 200
201 EEKSQKQNIDINRQAKFAATPSLALFVNLKNVVCKIGEDAEVLMSLYDPV 250
251 ESKFISENYLVRWSSSGLPKDIDRLHNLRAVFTDLGSKDLKREKISFVCQ 300
301 IVRVGRMELRDNNTRKLTSGLRRPFGVAVMDVTDIINGKVDDEDKQHFIP 350
351 FQPVAGENDFLQTVINKVIAAKEVNHKGQGLWVTLKLLPGDIHQIRKEFP 400
401 HLVDRTTAVARKTGFPEIIMPGDVRNDIYVTLVQGDFDKGSKTTAKNVEV 450
451 TVSVYDEDGKRLEHVIFPGAGDEAISEYKSVIYYQVKQPRWFETVKVAIP 500
501 IEDVNRSHLRFTFRHRSSQDSKDKSEKIFALAFVKLMRYDGTTLRDGEHD 550
551 LIVYKAEAKKLEDAATYLSLPSTKAELEEKGHSATGKSMQSLGSCTISKD 600
601 SFQISTLVCSTKLTQNVDLLGLLKWRSNTSLLQQNLRQLMKVDGGEVVKF 650
651 LQDTLDALFNIMMENSESETFDTLVFDALVFIIGLIADRKFQHFNPVLET 700
701 YIKKHFSATLAYTKLTKVLKNYVDGAEKPGVNEQLYKAMKALESIFKFIV 750
751 RSRILFNQLYENKGEADFVESLLQLFRSINDMMSSMSDQTVRVKGAALKY 800
801 LPTIVNDVKLVFDPKELSKMFTEFILNVPMGLLTIQKLYCLIEIVHSDLF 850
851 TQHDCREILLPMMTDQLKYHLERQEDLEACCQLLSHILEVLYRKDVGPTQ 900
901 RHVQIIMEKLLRTVNRTVISMGRDSELIGNFVACMTAILRQMEDYHYAHL 950
951 IKTFGKMRTDVVDFLMETFIMFKNLIGKNVYPFDWVIMNMVQNKVFLRAI 1000
1001 NQYADMLNKKFLDQANFELQLWNNYFHLAVAFLTQESLQLENFSSAKRAK 1050
1051 ILNKYGDMRRQIGFEIRDMWYNLGQHKIKFIPEMVGPILEMTLIPETELR 1100
1101 KATIPIFFDMMQCEFHSTRSFQMFENEIITKLDHEVEGGRGDEQYKVLFD 1150
1151 KILLEHCRKHKYLAKTGETFVKLVVRLMERLLDYRTIMHDENKENRMSCT 1200
1201 VNVLNFYKEIEREEMYIRYLYKLCDLHKECDNYTEAAYTLLLHAKLLKWS 1250
1251 EDVCVAHLTQRDGYQATTQGQLKEQLYQEIIHYFDKGKMWEEAIALGKEL 1300
1301 AEQYENEMFDYEQLSELLKKQAQFYENIVKVIRPKPDYFAVGYYGQGFPT 1350
1351 FLRGKVFIYRGKEYERREDFEARLLTQFPNAEKMKTTSPPGDDIKNSPGQ 1400
1401 YIQCFTVKPKLDLPPKFHRPVSEQIVSFYRVNEVQRFEYSRPIRKGEKNP 1450
1451 DNEFANMWIERTIYTTAYKLPGILRWFEVKSVFMVEISPLENAIETMQLT 1500
1501 NDKINSMVQQHLDDPSLPINPLSMLLNGIVDPAVMGGFANYEKAFFTDRY 1550
1551 LQEHPEAHEKIEKLKDLIAWQIPFLAEGIRIHGDKVTEALRPFHERMEAC 1600
1601 FKQLKEKVEKEYGVRIMPSSLDDRRGSRPRSMVRSFTMPSSSRPLSVASV 1650
1651 SSLSSDSTPSRPGSDGFALEPLLPKKMHSRSQDKLDKDDLEKEKKDKKKE 1700
1701 KRNSKHQEIFEKEFKPTDISLQQSEAVILSETISPLRPQRPKSQVMNVIG 1750
1751 SERRFSVSPSSPSSQQTPPPVTPRAKLSFSMQSSLELNGMTGADVADVPP 1800
1801 PLPLKGSVADYGNLMENQDLLGSPTPPPPPPHQRHLPPPLPSKTPPPPPP 1850
1851 KTTRKQASVDSGIVQ 1865
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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