Literature DB >> 26261224

SuccFind: a novel succinylation sites online prediction tool via enhanced characteristic strategy.

Hao-Dong Xu1, Shao-Ping Shi2, Ping-Ping Wen1, Jian-Ding Qiu3.   

Abstract

UNLABELLED: Lysine succinylation orchestrates a variety of biological processes. Annotation of succinylation in proteomes is the first-crucial step to decipher physiological roles of succinylation implicated in the pathological processes. In this work, we developed a novel succinylation site online prediction tool, called SuccFind, which is constructed to predict the lysine succinylation sites based on two major categories of characteristics: sequence-derived features and evolutionary-derived information of sequence and via an enhanced feature strategy for further optimizations. The assessment results obtained from cross-validation suggest that SuccFind can provide more instructive guidance for further experimental investigation of protein succinylation.
AVAILABILITY AND IMPLEMENTATION: A user-friendly server is freely available on the web at: http://bioinfo.ncu.edu.cn/SuccFind.aspx. CONTACT: jdqiu@ncu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 26261224     DOI: 10.1093/bioinformatics/btv439

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  19 in total

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5.  Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction.

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Authors:  Abdollah Dehzangi; Yosvany López; Sunil Pranit Lal; Ghazaleh Taherzadeh; Abdul Sattar; Tatsuhiko Tsunoda; Alok Sharma
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7.  Detecting Succinylation sites from protein sequences using ensemble support vector machine.

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Journal:  BMC Bioinformatics       Date:  2018-06-25       Impact factor: 3.169

8.  LSTMCNNsucc: A Bidirectional LSTM and CNN-Based Deep Learning Method for Predicting Lysine Succinylation Sites.

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10.  A systematic identification of species-specific protein succinylation sites using joint element features information.

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Journal:  Int J Nanomedicine       Date:  2017-08-28
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