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STM JOURNALS
I take the privilege to present the hard copy compilation for the Volume 3 Issue (3) of Research & Reviews: Journal of Computational Biology (RRJoCB). The intension of RRJoCB is to create an atmosphere that stimulates creativeness, research and growth in the area of Computational Biology. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. RRJoCB provides an outlet for Research findings and reviews in areas of Computational Biology found to be relevant for National and International recent developments & research initiative. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain of Computational Biology. Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for their continued support and invaluable contributions and suggestions in the form of authoring writeups/ reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviesw findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.
Dr. Archana Mehrotra Director STM Journals
Research & Reviews : Journal of Computational Biology
Contents
1. Phylogenetic Analysis of Antigenic Variability in Klebsiella pneumoniae against Antibacterial Ocular Drugs S. Umadevi, P. M. Ayyasamy, S. Rajakumar
1
2. Algorithm for Early Detection of Genetic Fusion in Cancer, Tumors and Chronic Bacterial Infection Ankush Rai
8
3. Statistical Implementation of the Plant Functional Traits of Bacopa monnieri and Their Biological Interpretation Shikha Suman
13
Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print) Volume 3, Issue 3 www.stmjournals.com
Phylogenetic Analysis of Antigenic Variability in Klebsiella pneumoniae against Antibacterial Ocular Drugs S. Umadevi 1, P. M. Ayyasamy2, S. Rajakumar1* 1
Department of Marine Biotechnology, Bharathidasan University, Tiruchirappalli, India 2 Department of Microbiology, Periyar University, Salem, India
Abstract Klebsiella pneumonia, associated with significant proportion of hospital-acquired urinary tract infections, pneumonia, soft tissue infections, liver abscess, endophthalmitis and meningitis. Though the antibiotic eye drops against K. pneumoniae are available, immunologically distinct strains evolved by mutations in epitopes and leads resistance to ocular antibacterial drugs. The analysis of escape mutation necessitates new drug development.Also, it constitutes a major challenge to effective drug design. In present work, molecular basis of antigenic resistance in K. pneumoniae against the antibacterial ocular drugs was investigated. The resistance genes were identified and identified that genetic drift was found in 16 genes and higher number of mutaionswas found in class-A beta-lactamase.The protein sequences of class-A beta-lactamase from resistance strains were obtained and antigenic variability was carried out in terms of antigenic distance based on the sequence alignment and phylogenetic analysis. Moreover the docking study of protein with drug molecules was done in order to find out whether the mutations are at active site or at other residues.It was found that, mutations were dispersed throughout the sequence, and were not found at a particular segment. The escape mutation was found less at active site than rest. It concludes that the mutations in non-active residues may leads to changes in electrostatic and steric interactions. In this work, drift was analyzed in class-A beta-lactamase alone, the overall analysis may play potential role in effective designing of antibacterial drug against K. pneumoniae.
Keywords: Antigenic variability, Class-A beta-lactamase, Klebsiella pneumonia, ocular drugs, phylogeny
RRJoCB (2014)Š STM Journals 2014. All Rights Reserved
Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print) Volume 3, Issue 3 www.stmjournals.com
Algorithm for Early Detection of Genetic Fusion in Cancer, Tumors and Chronic Bacterial Infection Ankush Rai* Department of Applied Science, CRIAD Laboratories, Smiriti Nagar, Bhilai 490020, Chhattisgarh, India Abstract In the present study we have designed an algorithm for early detection of DNA fusion to discover the potential transcription which embodies the fusion of gene products derivable from the human DNA with that of bacterial and cancerous viruses, resulting from the several breakage points and reassembling of different chromosomes, or that of within a chromosome. Without relying on existing annotations the proposed algorithm proves its efficacy in detecting alignment of RNA sequences from unannotated splice variants of known genome strands. Using this algorithm in the age of Big Data analytics the potential threat of cancer, tuberculosis, tumors, and asthma can be predicted beforehand while scaling such effects, ranging from individual to population scale. We have also reported the results of the algorithm for over 900 samples with solid supporting evidences and opens a new virotherapy approach of numerically quantized cure for disease like cancer, tumors and asthma.
Keywords: Algorithm, computational modeling, gene fusion, DNA transcription
RRJoCB (2014)Š STM Journals 2014. All Rights Reserved
Research & Reviews: Journal of Computational Biology ISSN: 2319-3433 (online), ISSN: 2349-3720 (print) Volume 3, Issue 3 www.stmjournals.com
Statistical Implementation of the Plant Functional Traits of Bacopa monnieri and Their Biological Interpretation Shikha Suman* Department of Botany, Banaras Hindu University, Varanasi, India Abstract The plat functional traits are interdependent and correlated, a single molecule or a smaller plant character may alter the whole physiology. This work is based on the statistical prove of the interdependence of the plant character in governing the life cycle and their biological interpretation. In this article, all the characters are statically correlated and depicted the main factors governing the prime function of the plant.
Keywords: Relative growth rate, correlation, biostatistical, plant functional traits
RRJoCB (2014)Š STM Journals 2014. All Rights Reserved