Literature DB >> 19276149

DV-Curve: a novel intuitive tool for visualizing and analyzing DNA sequences.

Zhu-Jin Zhang1.   

Abstract

MOTIVATION: The rapid growth of DNA sequence data creates a need to find graphic tools to study DNA sequence in a perceivable form. A large number of scholars work hard in this field. However, it is difficult to handle the following problems in one graph: (i) degeneracy, (ii) loss of information, (iii) difficulty of observing in multi-dimensional graph, (iv) difficulty of visualization when representing long DNA sequences and (v) need to reflect useful information.
RESULTS: DV-Curve (Dual-Vector Curve) using two vectors to represent one alphabet of DNA sequences not only avoids degeneracy and loss of information, but also has good visualization no matter whether sequences are long, and can reflect the length of DNA sequence. The applications of the DV-Curve on mutation analysis and two types of similarity analysis are presented in detail. DV-Curve is a significative tool by which biologists could find useful biological knowledge. AVAILABILITY: The corresponding software of DV-Curve is available at http://bmchust.3322.org/Data/Soft/332-DV-Curve2.0.zip.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19276149     DOI: 10.1093/bioinformatics/btp130

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


  9 in total

1.  Quantifying species diversity with a DNA barcoding-based method: Tibetan moth species (Noctuidae) on the Qinghai-Tibetan Plateau.

Authors:  Qian Jin; Huilin Han; XiMin Hu; XinHai Li; ChaoDong Zhu; Simon Y W Ho; Robert D Ward; Ai-bing Zhang
Journal:  PLoS One       Date:  2013-05-31       Impact factor: 3.240

2.  A new method for species identification via protein-coding and non-coding DNA barcodes by combining machine learning with bioinformatic methods.

Authors:  Ai-bing Zhang; Jie Feng; Robert D Ward; Ping Wan; Qiang Gao; Jun Wu; Wei-zhong Zhao
Journal:  PLoS One       Date:  2012-02-20       Impact factor: 3.240

3.  Sequence comparison via polar coordinates representation and curve tree.

Authors:  Qi Dai; Xiaodong Guo; Lihua Li
Journal:  J Theor Biol       Date:  2011-10-06       Impact factor: 2.691

4.  Three 3D graphical representations of DNA primary sequences based on the classifications of DNA bases and their applications.

Authors:  Guosen Xie; Zhongxi Mo
Journal:  J Theor Biol       Date:  2010-10-20       Impact factor: 2.691

5.  WalkIm: Compact image-based encoding for high-performance classification of biological sequences using simple tuning-free CNNs.

Authors:  Saeedeh Akbari Rokn Abadi; Amirhossein Mohammadi; Somayyeh Koohi
Journal:  PLoS One       Date:  2022-04-15       Impact factor: 3.752

6.  Multi-scale RNA comparison based on RNA triple vector curve representation.

Authors:  Ying Li; Ming Duan; Yanchun Liang
Journal:  BMC Bioinformatics       Date:  2012-10-30       Impact factor: 3.169

7.  DV-curve representation of protein sequences and its application.

Authors:  Wei Deng; Yihui Luan
Journal:  Comput Math Methods Med       Date:  2014-05-08       Impact factor: 2.238

8.  Similarity Estimation Between DNA Sequences Based on Local Pattern Histograms of Binary Images.

Authors:  Yusei Kobori; Satoshi Mizuta
Journal:  Genomics Proteomics Bioinformatics       Date:  2016-04-27       Impact factor: 7.691

9.  Protein Sequence Comparison and DNA-binding Protein Identification with Generalized PseAAC and Graphical Representation.

Authors:  Chun Li; Jialing Zhao; Changzhong Wang; Yuhua Yao
Journal:  Comb Chem High Throughput Screen       Date:  2018       Impact factor: 1.339

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.