scholarly journals Genomic Analysis of a Marine Bacterium: Bioinformatics for Comparison, Evaluation, and Interpretation of DNA Sequences

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Bhagwan N. Rekadwad ◽  
Juan M. Gonzalez ◽  
Chandrahasya N. Khobragade
Keyword(s):  
Dna Sequences ◽  
Marine Bacterium ◽  
Gc Content ◽  
Genomic Analysis ◽  
Principal Component ◽  
Genome Sequences ◽  
Qr Codes ◽  
Chaos Game Representation ◽  
Chaos Game ◽  
Game Representation

A total of five highly related strains of an unidentified marine bacterium were analyzed through their short genome sequences (AM260709–AM260713). Genome-to-Genome Distance (GGDC) showed high similarity to Pseudoalteromonas haloplanktis (X67024). The generated unique Quick Response (QR) codes indicated no identity to other microbial species or gene sequences. Chaos Game Representation (CGR) showed the number of bases concentrated in the area. Guanine residues were highest in number followed by cytosine. Frequency of Chaos Game Representation (FCGR) indicated that CC and GG blocks have higher frequency in the sequence from the evaluated marine bacterium strains. Maximum GC content for the marine bacterium strains ranged 53-54%. The use of QR codes, CGR, FCGR, and GC dataset helped in identifying and interpreting short genome sequences from specific isolates. A phylogenetic tree was constructed with the bootstrap test (1000 replicates) using MEGA6 software. Principal Component Analysis (PCA) was carried out using EMBL-EBI MUSCLE program. Thus, generated genomic data are of great assistance for hierarchical classification in Bacterial Systematics which combined with phenotypic features represents a basic procedure for a polyphasic approach on unambiguous bacterial isolate taxonomic classification.

scholarly journals APPLICATION OF CHAOS GAME REPRESENTATION TO NONLINEAR TIME SERIES ANALYSIS

Fractals ◽  
2006 ◽  
Vol 14 (01) ◽  
pp. 27-35 ◽  
Author(s):  
TOMOYA SUZUKI ◽  
TOHRU IKEGUCHI ◽  
MASUO SUZUKI
Keyword(s):  
Time Series ◽  
Real Time ◽  
Dna Sequences ◽  
Surrogate Data ◽  
Nonlinear Time Series Analysis ◽  
Conditional Probabilities ◽  
Fractal Structures ◽  
Chaos Game Representation ◽  
Chaos Game ◽  
Game Representation

Iterative function systems are often used for investigating fractal structures. The method is also referred as Chaos Game Representation (CGR), and is applied for representing characteristic structures of DNA sequences visually. In this paper, we proposed an original way of plotting CGR to easily confirm the property of the temporal evaluation of a time series. We also showed existence of spurious characteristic structures of time series, if we carelessly applied the CGR to real time series. We revealed that the source of spurious identification came from non-uniformity of the frequency histograms of the time series, which is often the case of analyzing real time series. We also showed how to avoid such spurious identification by applying the method of surrogate data and introducing conditional probabilities of the time series.

scholarly journals k-mer proximity index for phylogeny comparison of SARS-CoV-2 with other pathogens

2020 ◽  
Author(s):  
Pratibha ◽  
Cyril Shaju ◽  
Kamal ◽  
Aman Gupta
Keyword(s):  
Treatment Strategy ◽  
In Silico ◽  
Nucleotide Sequences ◽  
Macro Level ◽  
Genome Sequences ◽  
Inexpensive Method ◽  
Chaos Game Representation ◽  
Chaos Game ◽  
Proximity Index ◽  
Game Representation

Abstract We developed a compact and computationally inexpensive method for in-silico comparison of nucleotide sequences at a macro level using subtraction-percentage plots (SP-plots) of a modified chaos game representation (CGR). Analyzing these plots, we defined the k-mer proximity index quantifying the differences between SARS-CoV-2 and other pathogens’ genome sequences. We categorized 31 pathogens, on the basis of their proximity to SARS-CoV-2, in four groups to possibly plan a treatment strategy for Covid-19.

Sign in / Sign up

Export Citation Format

Share Document