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Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques
The DNA-protein interactions play vital roles in the central dogma of molecular biology. Proper interactions between DNA and protein would lead to the onset of various biological phenomena like transcription, translation, and replication. However, the mechanisms of these well-known processes vary be...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137564/ https://www.ncbi.nlm.nih.gov/pubmed/30237677 http://dx.doi.org/10.6026/97320630014315 |
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author | Nilkanta, Chowdhury Bagchi, Angshuman |
author_facet | Nilkanta, Chowdhury Bagchi, Angshuman |
author_sort | Nilkanta, Chowdhury |
collection | PubMed |
description | The DNA-protein interactions play vital roles in the central dogma of molecular biology. Proper interactions between DNA and protein would lead to the onset of various biological phenomena like transcription, translation, and replication. However, the mechanisms of these well-known processes vary between prokaryotic and eukaryotic organisms. The exact molecular mechanisms of these processes are unknown. Therefore, it is of interest to report the comparative estimate of the different properties of the DNA binding proteins from prokaryotic and eukaryotic organisms. We analyzed the different sequence-based features such as the frequency of amino acids and amino acid groups in the proteins of prokaryotes and eukaryotes by statistical measures. The general pattern of differences between the various DNA binding proteins for the development of a prediction system to discriminate between these proteins between prokaryotes and eukaryotes is documented. |
format | Online Article Text |
id | pubmed-6137564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-61375642018-09-20 Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques Nilkanta, Chowdhury Bagchi, Angshuman Bioinformation Hypothesis The DNA-protein interactions play vital roles in the central dogma of molecular biology. Proper interactions between DNA and protein would lead to the onset of various biological phenomena like transcription, translation, and replication. However, the mechanisms of these well-known processes vary between prokaryotic and eukaryotic organisms. The exact molecular mechanisms of these processes are unknown. Therefore, it is of interest to report the comparative estimate of the different properties of the DNA binding proteins from prokaryotic and eukaryotic organisms. We analyzed the different sequence-based features such as the frequency of amino acids and amino acid groups in the proteins of prokaryotes and eukaryotes by statistical measures. The general pattern of differences between the various DNA binding proteins for the development of a prediction system to discriminate between these proteins between prokaryotes and eukaryotes is documented. Biomedical Informatics 2018-06-30 /pmc/articles/PMC6137564/ /pubmed/30237677 http://dx.doi.org/10.6026/97320630014315 Text en © 2018 Biomedical Informatics http://creativecommons.org/licenses/by/3.0/ This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Hypothesis Nilkanta, Chowdhury Bagchi, Angshuman Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title | Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title_full | Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title_fullStr | Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title_full_unstemmed | Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title_short | Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
title_sort | comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques |
topic | Hypothesis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137564/ https://www.ncbi.nlm.nih.gov/pubmed/30237677 http://dx.doi.org/10.6026/97320630014315 |
work_keys_str_mv | AT nilkantachowdhury comparativeanalysisofprokaryoticandeukaryotictranscriptionfactorsusingmachinelearningtechniques AT bagchiangshuman comparativeanalysisofprokaryoticandeukaryotictranscriptionfactorsusingmachinelearningtechniques |