GPS-YNO2 protocols

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GPS-YNO2 specifications

Information


Unique identifier OMICS_09963
Name GPS-YNO2
Software type Application/Script
Interface Graphical user interface
Restrictions to use Academic or non-commercial use
Input data A primary sequence or multiple proteins sequences.
Input format FASTA
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Medium
Version 1.0.1
Stability Stable
Maintained Yes

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Documentation


Maintainers


  • person_outline Jian Ren <>
  • person_outline Yu Xue <>
  • person_outline Dr. Zexian Liu <>

Additional information


http://yno2.biocuckoo.org/faq.php

Information


Unique identifier OMICS_09963
Name GPS-YNO2
Interface Web user interface
Restrictions to use Academic or non-commercial use
Input data A primary sequence or multiple proteins sequences.
Input format FASTA
Computer skills Basic
Stability Stable
Requirements
JRE
Maintained Yes

Documentation


Maintainers


  • person_outline Jian Ren <>
  • person_outline Yu Xue <>
  • person_outline Dr. Zexian Liu <>

Additional information


http://yno2.biocuckoo.org/faq.php

Publication for GPS-YNO2

GPS-YNO2 in pipeline

2014
PMCID: 4204854
PMID: 25333472
DOI: 10.1371/journal.pone.0110232

[…] used in this field include igps 1.0, which is used to predict phosphorylation , css-palm 4.0, which is used to predict s-palmitoylation , gps-sumo 1.0, which is used to predict sumoylation , and gps-yno2, which is used to predict protein nitration . moreover, several programs and algorithms have been developed to predict cysteine residues that are susceptible to s-nitrosylation, including […]


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GPS-YNO2 in publications

 (5)
PMCID: 5647517
PMID: 29062872
DOI: 10.1016/j.dib.2017.09.058

[…] were challenged with an olive pollen transcriptome described in the reprolive database (http://reprolive.eez.csic.es) using different thresholds, when available. for tyr-nitration prediction, the gps-yno2 (http://yno2.biocuckoo.org) tool was used instead, also using two different thresholds. bioinformatic analysis pipelines were adapted to integrate the use of such bionformatic tools […]

PMCID: 5410141
PMID: 28462053
DOI: 10.7717/peerj.3261

[…] of 40 o-glcnacylation sites. later, a svm-based model named o-glcnacpred was developed for capturing potential o-glcnacylation sites (). meanwhile, provided the online service and local package of gps-yno2 1.0 for identification of tyrosine nitration with the previously developed gps algorithm () and sequence information. recently, developed a predictor termed gps-tsp for the prediction […]

PMCID: 4204854
PMID: 25333472
DOI: 10.1371/journal.pone.0110232

[…] used in this field include igps 1.0, which is used to predict phosphorylation , css-palm 4.0, which is used to predict s-palmitoylation , gps-sumo 1.0, which is used to predict sumoylation , and gps-yno2, which is used to predict protein nitration . moreover, several programs and algorithms have been developed to predict cysteine residues that are susceptible to s-nitrosylation, including […]

PMCID: 3603447
PMID: 23389939
DOI: 10.1098/rsob.120148

[…] conditions and has been shown to alter protein function. whether 3-nitrotyrosine is important in normal cellular processes or is likely to affect specific biological pathways remains unclear. using gps-yno2, a recently described 3-nitrotyrosine prediction algorithm, a set of predictions for nitrated residues in the human proteome was generated. in total, 9.27 per cent of the proteome […]

PMCID: 3279363
PMID: 22348091
DOI: 10.1371/journal.pone.0031483

[…] using delphi and mapped with the chimera program to 1bv1. most of the targetable groups, with the exception of y66, are in a negative environment, which favours nitration. we subsequently applied gps-yno2 , a recently developed predictor for potential nitration sites based on sequence information. the predictor ranks y150 and y158 with the highest scores, but also the inaccessible y120 […]


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GPS-YNO2 institution(s)
Life Sciences School, Sun Yat-sen University (SYSU), Guangzhou, China; Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, Hefei, Anhui, China; Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
GPS-YNO2 funding source(s)
Supported by grants from the National Basic Research Program (973 project) (2010CB945400), National Natural Science Foundation of China (90919001, 30700138, 30900835, 30830036, 30900835, 31071154), Chinese Academy of Sciences (INFO-115-C01-SDB4-36) and HUST Innovative Program (2010ZD018).

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