Literature DB >> 26099739

Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences.

Wei Chen1, Hao Lin, Kuo-Chen Chou.   

Abstract

With the avalanche of DNA/RNA sequences generated in the post-genomic age, it is urgent to develop automated methods for analyzing the relationship between the sequences and their functions. Towards this goal, a series of sequence-based methods have been proposed and applied to analyze various character-unknown DNA/RNA sequences in order for in-depth understanding their action mechanisms and processes. Compared with the classical sequence-based methods, the pseudo nucleotide composition or PseKNC approach developed very recently has the following advantages: (1) it can convert length-different DNA/RNA sequences into dimension-fixed digital vectors that can be directly handled by all the existing machine-learning algorithms or operation engines; (2) it can contain the desired features and properties according to the selection or definition of users; (3) it can cover considerable sequence pattern information, both local and global. This minireview is focused on the concept of pseudo nucleotide composition, its development and applications.

Entities:  

Mesh:

Year:  2015        PMID: 26099739     DOI: 10.1039/c5mb00155b

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  62 in total

1.  iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples.

Authors:  Muhammad Kabir; Maqsood Hayat
Journal:  Mol Genet Genomics       Date:  2015-08-30       Impact factor: 3.291

2.  MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.

Authors:  Meng Zhang; Fuyi Li; Tatiana T Marquez-Lago; André Leier; Cunshuo Fan; Chee Keong Kwoh; Kuo-Chen Chou; Jiangning Song; Cangzhi Jia
Journal:  Bioinformatics       Date:  2019-09-01       Impact factor: 6.937

3.  Predicting membrane proteins and their types by extracting various sequence features into Chou's general PseAAC.

Authors:  Ahmad Hassan Butt; Nouman Rasool; Yaser Daanial Khan
Journal:  Mol Biol Rep       Date:  2018-09-20       Impact factor: 2.316

Review 4.  Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs.

Authors:  Qiu-Xing Jiang
Journal:  Med Chem       Date:  2019       Impact factor: 2.745

5.  Evolutionary mechanism and biological functions of 8-mers containing CG dinucleotide in yeast.

Authors:  Yan Zheng; Hong Li; Yue Wang; Hu Meng; Qiang Zhang; Xiaoqing Zhao
Journal:  Chromosome Res       Date:  2017-02-09       Impact factor: 5.239

Review 6.  Some illuminating remarks on molecular genetics and genomics as well as drug development.

Authors:  Kuo-Chen Chou
Journal:  Mol Genet Genomics       Date:  2020-01-01       Impact factor: 3.291

7.  Comparison of genomic data via statistical distribution.

Authors:  Saeid Amiri; Ivo D Dinov
Journal:  J Theor Biol       Date:  2016-07-25       Impact factor: 2.691

8.  i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation.

Authors:  Md Mehedi Hasan; Balachandran Manavalan; Watshara Shoombuatong; Mst Shamima Khatun; Hiroyuki Kurata
Journal:  Plant Mol Biol       Date:  2020-03-05       Impact factor: 4.076

9.  A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome.

Authors:  Chowdhury Rafeed Rahman; Ruhul Amin; Swakkhar Shatabda; Md Sadrul Islam Toaha
Journal:  Sci Rep       Date:  2021-05-14       Impact factor: 4.379

10.  CNNLSTMac4CPred: A Hybrid Model for N4-Acetylcytidine Prediction.

Authors:  Guiyang Zhang; Wei Luo; Jianyi Lyu; Zu-Guo Yu; Guohua Huang
Journal:  Interdiscip Sci       Date:  2022-02-01       Impact factor: 2.233

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.