Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS

Angela Uche Makolo

doi:doi:10.11648/j.cbb.20190701.11

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Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS

Angela Uche Makolo

Published in Computational Biology and Bioinformatics (Volume 7, Issue 1)

Received: 2 February 2019 Accepted: 22 March 2019 Published: 18 April 2019

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Abstract

The understanding of the relationship of a gene with other genes in its neighbourhood and the implication of this relationship on the biochemical activities of the entire genome need an efficient computational tool to unfold the relationship. GENAVIS: (GENe Adjacency VIsualization Software) is an open source, platform independent web-based software for modeling neighborhood genes as binary codes. We also incorporated the feature of having an interactive visual representation of patterns of the binary code for a specific gene family in multiple microbial genomes. The concept of using binary code for representation is derived from computational thinking techniques which models problems using computer logic of applying abstraction and pattern matching to extract hidden patterns aimed at knowledge discovery. The result provides an insight into the analysis of transcriptional unit with more than one gene and genes encoding for universal stress protein, which also allows for a comparative analysis of multiple genomes as the basis for biosynthetic pathways and multi-gene function prediction.

Published in	Computational Biology and Bioinformatics (Volume 7, Issue 1)
DOI	10.11648/j.cbb.20190701.11
Page(s)	1-4
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Neighbourhood, Adjacency, Transcription Direction, Universal Stress Protein, Binary Code

References

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[2]	Baraka S. Williams, Raphael D. Isokpehi, Andreas N. Mbah, Antoinesha L. Hollman, Christina O. Bernard, 1Shaneka S. Simmons, Wellington K. Ayensu, and Bianca L. Garner. Functional Annotation Analytics of Bacillus Genomes Reveals Stress Responsive Acetate Utilization and Sulfate Uptake in the Biotechnologically Relevant Bacillus megaterium. BioinformBiol Insights. 2012; 6:275-86. doi: 10.4137/BBI.S7977. Epub 2012 Nov 21.
[3]	Chen Y., Zhang Z., Zheng J., Maa Y. and Xue Y. (2017). Gene selection for tumor classification using neighborhood rough sets and entropy measures. Journal of Biomedical Informatics 67 (2017) 59–68. http://dx.doi.org/10.1016/j.jbi.2017.02.007.
[4]	Hou M., Wang S., Li X. and Lei Y. (2009). Neighborhood Rough Set Reduction-Based Gene Selection and Prioritization for Gene Expression Profile Analysis and Molecular Cancer Classification. Journal of Biomedicine and Biotechnology. Volume 2010, Article ID 726413, 12 pages doi:10.1155/2010/726413.
[5]	Jiang W., Sun l., Yang X., Wang M., Esmaeili N., Pehlivan N., Zhao R., Zhang H. and Zhao Y. (2017). The Effects of Transcription Directions of Transgenes and the gypsy Insulators on the Transcript Levels of Transgenes in Transgenic Arabidopsis. Scientific Reports \| 7: 14757 \| DOI:10.1038/s41598-017-15284-x.
[6]	Jones R (2010) There Goes the (Gene Expression) Neighbourhood Theory. PLoS Biol 8(11): e1001002. doi:10.1371/journal.pbio.1001002.
[7]	L. Martinez-Martinez et al., Clinical significance of Corynebacterium striatum isolated from human sample, Clin Microbiol Infect. 1997 Feb; 3(6):634-639.
[8]	Larkin J. D., Cook P. R., and Papantonis A. (2012). Dynamic Reconfiguration of Long Human Genes during One Transcription Cycle. Molecular and Cellular Biology. Volume 32 Number 14. p. 2738–2747.
[9]	Makolo Angela and Isokpehi Raphael (2015): Interactive Visual Representations of Gene Transcriptional Direction Patterns in Microbial Genomes. European Molecular Biology Organization Conference on Visualization of Biological Data, VISBI 2015, USA. http://vizbi.org/Posters/2015/B10.
[10]	Oliver B., Parisi M. and Clark D. (2002). Gene expression neighborhoods. Journal of Biology 2002, Volume 1, Issue 1, Article 4. http://jbiol.com/content/1/1/4.
[11]	Srivatsan A, Tehranchi A, MacAlpine DM, Wang JD (2010) Co-Orientation of Replication and Transcription Preserves Genome Integrity. PLoS Genet 6(1): e1000810. doi:10.1371/journal.pgen.1000810.
[12]	Tremonte P., Succi M., Coppola R., Sorrentino E., Tipaldi L., Picariello G., Pannella G. and Fraternali F. (2016) Homology-Based Modeling of Universal Stress Protein from Listeria innocua Up-Regulated under Acid Stress Conditions. Front. Microbiol.7:1998. doi: 10.3389/fmicb.2016.01998.

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APA Style

Angela Uche Makolo. (2019). Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Computational Biology and Bioinformatics, 7(1), 1-4. https://doi.org/10.11648/j.cbb.20190701.11

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ACS Style

Angela Uche Makolo. Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Comput. Biol. Bioinform. 2019, 7(1), 1-4. doi: 10.11648/j.cbb.20190701.11

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AMA Style

Angela Uche Makolo. Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Comput Biol Bioinform. 2019;7(1):1-4. doi: 10.11648/j.cbb.20190701.11

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@article{10.11648/j.cbb.20190701.11,
  author = {Angela Uche Makolo},
  title = {Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS},
  journal = {Computational Biology and Bioinformatics},
  volume = {7},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.cbb.20190701.11},
  url = {https://doi.org/10.11648/j.cbb.20190701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20190701.11},
  abstract = {The understanding of the relationship of a gene with other genes in its neighbourhood and the implication of this relationship on the biochemical activities of the entire genome need an efficient computational tool to unfold the relationship. GENAVIS: (GENe Adjacency VIsualization Software) is an open source, platform independent web-based software for modeling neighborhood genes as binary codes. We also incorporated the feature of having an interactive visual representation of patterns of the binary code for a specific gene family in multiple microbial genomes. The concept of using binary code for representation is derived from computational thinking techniques which models problems using computer logic of applying abstraction and pattern matching to extract hidden patterns aimed at knowledge discovery. The result provides an insight into the analysis of transcriptional unit with more than one gene and genes encoding for universal stress protein, which also allows for a comparative analysis of multiple genomes as the basis for biosynthetic pathways and multi-gene function prediction.},
 year = {2019}
}

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TY  - JOUR
T1  - Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS
AU  - Angela Uche Makolo
Y1  - 2019/04/18
PY  - 2019
N1  - https://doi.org/10.11648/j.cbb.20190701.11
DO  - 10.11648/j.cbb.20190701.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 1
EP  - 4
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20190701.11
AB  - The understanding of the relationship of a gene with other genes in its neighbourhood and the implication of this relationship on the biochemical activities of the entire genome need an efficient computational tool to unfold the relationship. GENAVIS: (GENe Adjacency VIsualization Software) is an open source, platform independent web-based software for modeling neighborhood genes as binary codes. We also incorporated the feature of having an interactive visual representation of patterns of the binary code for a specific gene family in multiple microbial genomes. The concept of using binary code for representation is derived from computational thinking techniques which models problems using computer logic of applying abstraction and pattern matching to extract hidden patterns aimed at knowledge discovery. The result provides an insight into the analysis of transcriptional unit with more than one gene and genes encoding for universal stress protein, which also allows for a comparative analysis of multiple genomes as the basis for biosynthetic pathways and multi-gene function prediction.
VL  - 7
IS  - 1
ER  -

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Author Information

Angela Uche Makolo

Department of Computer Science, University of Ibadan, Ibadan, Nigeria

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APA Style

Angela Uche Makolo. (2019). Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Computational Biology and Bioinformatics, 7(1), 1-4. https://doi.org/10.11648/j.cbb.20190701.11

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ACS Style

Angela Uche Makolo. Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Comput. Biol. Bioinform. 2019, 7(1), 1-4. doi: 10.11648/j.cbb.20190701.11

Copy | Download

AMA Style

Angela Uche Makolo. Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS. Comput Biol Bioinform. 2019;7(1):1-4. doi: 10.11648/j.cbb.20190701.11

Copy | Download

@article{10.11648/j.cbb.20190701.11,
  author = {Angela Uche Makolo},
  title = {Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS},
  journal = {Computational Biology and Bioinformatics},
  volume = {7},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.cbb.20190701.11},
  url = {https://doi.org/10.11648/j.cbb.20190701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20190701.11},
  abstract = {The understanding of the relationship of a gene with other genes in its neighbourhood and the implication of this relationship on the biochemical activities of the entire genome need an efficient computational tool to unfold the relationship. GENAVIS: (GENe Adjacency VIsualization Software) is an open source, platform independent web-based software for modeling neighborhood genes as binary codes. We also incorporated the feature of having an interactive visual representation of patterns of the binary code for a specific gene family in multiple microbial genomes. The concept of using binary code for representation is derived from computational thinking techniques which models problems using computer logic of applying abstraction and pattern matching to extract hidden patterns aimed at knowledge discovery. The result provides an insight into the analysis of transcriptional unit with more than one gene and genes encoding for universal stress protein, which also allows for a comparative analysis of multiple genomes as the basis for biosynthetic pathways and multi-gene function prediction.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Transcription Direction Patterns of Adjacent Genes in Mycobacterium Tuberculosis Using GENAVIS
AU  - Angela Uche Makolo
Y1  - 2019/04/18
PY  - 2019
N1  - https://doi.org/10.11648/j.cbb.20190701.11
DO  - 10.11648/j.cbb.20190701.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 1
EP  - 4
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20190701.11
AB  - The understanding of the relationship of a gene with other genes in its neighbourhood and the implication of this relationship on the biochemical activities of the entire genome need an efficient computational tool to unfold the relationship. GENAVIS: (GENe Adjacency VIsualization Software) is an open source, platform independent web-based software for modeling neighborhood genes as binary codes. We also incorporated the feature of having an interactive visual representation of patterns of the binary code for a specific gene family in multiple microbial genomes. The concept of using binary code for representation is derived from computational thinking techniques which models problems using computer logic of applying abstraction and pattern matching to extract hidden patterns aimed at knowledge discovery. The result provides an insight into the analysis of transcriptional unit with more than one gene and genes encoding for universal stress protein, which also allows for a comparative analysis of multiple genomes as the basis for biosynthetic pathways and multi-gene function prediction.
VL  - 7
IS  - 1
ER  -

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