Phylogenetic Tree Construction for DNA Sequences using Clustering Methods

Mahapatro, Gayatri; Mishra, Debahuti; Shaw, Kailash; Mishra, Sashikala; Jena, Tanushree

doi:10.1016/j.proeng.2012.06.169

Cited by 13 publications

(10 citation statements)

References 7 publications

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“…Phylogenetic analysis (Figure 1), shows the kinship between Bacillus bacteria isolated from the fish intestine which consists of one cluster and three subclusters. Clustering is a method that divides a set of data into a similar set of subclasses and has meaning in a phylogenetic tree construction (Mahaputro et al, 2012, Adolfsson et al, 2018. Through the help of clustering analysis, genetic relationships between samples can be more easily understood.…”

Section: Resultsmentioning

confidence: 99%

Molecular Identification of Bacillus Derived from the Common Carp Intestine and Their Antibiotics Resistance

Mulyani¹,

Syakirotin²,

Haetami³

et al. 2020

Jurnal Biodjati

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The use of bacteria as a biological control agent in aquaculture is such new hope overcoming the negative impacts of the impropriate use of antibiotics. Bacillus is widely known as a potential probiotic for aquaculture, especially which are derived from aquatic biota. Due to a concern that the role of Bacillus as a probiotic agent will be disrupted by residues of antibiotics in the water, this research aimed to identify Bacillus species from common carp intestine based on the molecular method and investigate their resistance to some com-mercial antibiotics that widely used in aquaculture. Chloramphenicol, ampicillin, and metronidazole were used to determine the Bacillus resistance to antibiotics using the Kirby Bauer method. The resistance assay was carried out with a bacterial density of 108 CFU/mL. The results showed that Bacillus isolates derived from common carp intestine were closely related and resistant to antibiotics. Isolates that resistant to the three types of antibiotics were Cc.1.9 (CgN9) and Cc.2.18 (CgM18).

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Section: Resultsmentioning

confidence: 99%

Molecular Identification of Bacillus Derived from the Common Carp Intestine and Their Antibiotics Resistance

Mulyani¹,

Syakirotin²,

Haetami³

et al. 2020

Jurnal Biodjati

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“…The protein sequences of the Arabidopsis LIM genes were acquired from TAIR (, accessed date: 11 August 2018) and those of the rice and maize LIM genes were acquired from the Phytozome database (, accessed date: 11 August 2018). In order to investigate the evolutionary relationships among the LIM domain proteins in different plant species, aphylogenetic tree was constructed [69]. All Arabidopsis , rice, maize and foxtail millet LIM protein sequences were imported using MEGA7.0 [70], and multiple sequence alignments were performed using ClustalW with the default multiple alignment parameters.…”

Section: Methodsmentioning

confidence: 99%

Genome-Wide Analysis of LIM Family Genes in Foxtail Millet (Setaria italica L.) and Characterization of the Role of SiWLIM2b in Drought Tolerance

Yang

Chen

Sun

et al. 2019

IJMS

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LIM proteins have been found to play important roles in many life activities, including the regulation of gene expression, construction of the cytoskeleton, signal transduction and metabolic regulation. Because of their important roles in many aspects of plant development, LIM genes have been studied in many plant species. However, the LIM gene family has not yet been characterized in foxtail millet. In this study, we analyzed the whole genome of foxtail millet and identified 10 LIM genes. All LIM gene promoters contain MYB and MYC cis-acting elements that are related to drought stress. Based on the presence of multiple abiotic stress-related cis-elements in the promoter of SiWLIM2b, we chose this gene for further study. We analyzed SiWLIM2b expression under abiotic stress and hormone treatments using qRT-PCR. We found that SiWLIM2b was induced by various abiotic stresses and hormones. Under drought conditions, transgenic rice of SiWLIM2b-overexpression had a higher survival rate, higher relative water content and less cell damage than wild type (WT) rice. These results indicate that overexpression of the foxtail millet SiWLIM2b gene enhances drought tolerance in transgenic rice, and the SiWLIM2b gene can potentially be used for molecular breeding of crops with increased resistance to abiotic stress.

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“…Also, machine learning-based methods have been used to deal with genomic data to identify biomarkers for diseases and to identify therapeutic targets [98,99]. While traditionally in bioinformatics one performs nucleotide sequence comparison with techniques such as BLAST to also understand evolutionary relationships, machine learning-based methods have also been developed to perform phylogenetic tree construction and classification and also taxonomic classification from DNA sequence [100][101][102]. In the proteomics space, deep learning tools have also been developed wherein given the amino acid sequence the deep learning tool predicts the protein structure and function [103,104]…”

Section: 2mentioning

confidence: 99%

Recent advances in the application of data science and machine/deep learning methods to research in chemical and biological sciences : a review

S¹

2020

Preprint

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The rise in application of methods of data science and machine/deep learning in chemical and biological sciences must be discussed in the light of the fore-running disciplines of bio/chem-informatics and computational chemistry and biology which helped in the accumulation ofenormous research data because of which successful application of data-driven approaches have been made possible now. Many of the tasks and goals of Ab initio methods in computational chemistry such as determination of optimized structure and other molecular properties of atoms, molecules, and compounds are being carried out with much lesser computational cost with data-driven machine/deep learning-based predictions. One observes a similar trend in computational biology, wherein, data-driven machine/deep learning methods are being proposed to predict the structure and dynamical of interactions of biological macromolecules such as proteins and DNA over computational expensive molecular dynamics based methods. In the cheminformatics space,one sees the rise of deep neural network-based methods that have scaled traditional structure-property/structure-activity to handle big data to design new materials with desired property and drugs with required activity in deep learning-based de novo molecular design methods. In thebioinformatics space, data-driven machine/deep learning approaches to genomic and proteomic data have led to interesting applications in fields such as precision medicine, prognosis prediction, and more. Thus the success story of the application of data science, machine/deep learning, andartificial intelligence to the disciple of chem/bio-informatics, and computational chemistry and biology has been told in light of how these fore-running disciplines had created huge repositories of data for data-driven approaches to be successful in these disciplines.

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Phylogenetic Tree Construction for DNA Sequences using Clustering Methods

Cited by 13 publications

References 7 publications

Molecular Identification of Bacillus Derived from the Common Carp Intestine and Their Antibiotics Resistance

Molecular Identification of Bacillus Derived from the Common Carp Intestine and Their Antibiotics Resistance

Genome-Wide Analysis of LIM Family Genes in Foxtail Millet (Setaria italica L.) and Characterization of the Role of SiWLIM2b in Drought Tolerance

Recent advances in the application of data science and machine/deep learning methods to research in chemical and biological sciences : a review

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