iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC

被引:249
作者
Feng, Pengmian [1 ]
Yang, Hui [2 ]
Ding, Hui [2 ]
Lin, Hao [2 ,5 ]
Chen, Wei [3 ,4 ,5 ]
Chou, Kuo-Chen [2 ,5 ]
机构
[1] North China Univ Sci & Technol, Hebei Prov Key Lab Occupat Hlth & Safety Coal Ind, Sch Publ Hlth, Tangshan 063000, Peoples R China
[2] Univ Elect Sci & Technol China, Key Lab Neuroinformat, Sch Life Sci & Technol, Minist Educ,Ctr Informat Biol, Chengdu 610054, Sichuan, Peoples R China
[3] North China Univ Sci & Technol, Dept Phys, Sch Sci, Tangshan 063000, Peoples R China
[4] North China Univ Sci & Technol, Ctr Genom & Computat Biol, Tangshan 063000, Peoples R China
[5] Gordon Life Sci Inst, Boston, MA 02478 USA
基金
中国博士后科学基金;
关键词
PTMs; N-6-methyladenine; Nucleotide physicochemical properties; General PseKNC; Lingering density; Intuitive metrics; AMINO-ACID-COMPOSITION; SEQUENCE-BASED PREDICTOR; MEMBRANE-PROTEIN TYPES; LYSINE SUCCINYLATION SITES; LABEL LEARNING CLASSIFIER; SUPPORT VECTOR MACHINES; SUBCELLULAR-LOCALIZATION; K-TUPLE; RECOMBINATION SPOTS; STRUCTURAL CLASS;
D O I
10.1016/j.ygeno.2018.01.005
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
N-6-methyladenine (6mA) is one kind of post-replication modification (PTM or PTRM) occurring in a wide range of DNA sequences. Accurate identification of its sites will be very helpful for revealing the biological functions of 6mA, but it is time-consuming and expensive to determine them by experiments alone. Unfortunately, so far, no bioinformatics tool is available to do so. To fill in such an empty area, we have proposed a novel predictor called iDNA6mA-PseKNC that is established by incorporating nucleotide physicochemical properties into Pseudo K-tuple Nucleotide Composition (PseKNC). It has been observed via rigorous cross-validations that the predictor's sensitivity (Sn), specificity (Sp), accuracy (Acc), and stability (MCC) are 93%, 100%, 96%, and 0.93, respectively. For the convenience of most experimental scientists, a user-friendly web server for iDNA6mA-PseKNC has been established at http://lin-group.cn/server/iDNA6mA-PseKNC, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.
引用
收藏
页码:96 / 102
页数:7
相关论文
共 154 条
[1]   Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition [J].
Ahmad, Khurshid ;
Waris, Muhammad ;
Hayat, Maqsood .
JOURNAL OF MEMBRANE BIOLOGY, 2016, 249 (03) :293-304
[2]   Identification of Heat Shock Protein families and J-protein types by incorporating Dipeptide Composition into Chou's general PseAAC [J].
Ahmad, Saeed ;
Kabir, Muhammad ;
Hayat, Maqsood .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2015, 122 (02) :165-174
[3]   Classification of membrane protein types using Voting Feature Interval in combination with Chou's Pseudo Amino Acid Composition [J].
Ali, Farman ;
Hayat, Maqsood .
JOURNAL OF THEORETICAL BIOLOGY, 2015, 384 :78-83
[4]  
[Anonymous], MOL INF
[5]  
[Anonymous], INTRO SUPPORT VECTOR
[6]   Analysis and comparison of lignin peroxidases between fungi and bacteria using three different modes of Chou's general pseudo amino acid composition [J].
Behbahani, Mandana ;
Mohabatkar, Hassan ;
Nosrati, Mokhtar .
JOURNAL OF THEORETICAL BIOLOGY, 2016, 411 :1-5
[7]   Using LogitBoost classifier to predict protein structural classes [J].
Cai, YD ;
Feng, KY ;
Lu, WC ;
Chou, KC .
JOURNAL OF THEORETICAL BIOLOGY, 2006, 238 (01) :172-176
[8]   Support vector machines for predicting membrane protein types by using functional domain composition [J].
Cai, YD ;
Zhou, GP ;
Chou, KC .
BIOPHYSICAL JOURNAL, 2003, 84 (05) :3257-3263
[9]   ESCHERICHIA-COLI ORIC AND THE DNAA GENE PROMOTER ARE SEQUESTERED FROM DAM METHYLTRANSFERASE FOLLOWING THE PASSAGE OF THE CHROMOSOMAL REPLICATION FORK [J].
CAMPBELL, JL ;
KLECKNER, N .
CELL, 1990, 62 (05) :967-979
[10]   propy: a tool to generate various modes of Chou's PseAAC [J].
Cao, Dong-Sheng ;
Xu, Qing-Song ;
Liang, Yi-Zeng .
BIOINFORMATICS, 2013, 29 (07) :960-962