scholarly journals Comparative Functional Genomics Studies for Understanding the Hypothetical Proteins in Mycobacterium tuberculosis KZN 1435

2012 ◽  
Vol 60 (1) ◽  
pp. 1-3
Author(s):  
Swapnil Sanmukh ◽  
Sumita Goswami ◽  
Sandhya Swaminathan ◽  
Waman Paunikar
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Functional Genomics ◽  
Hypothetical Proteins ◽  
Comparative Functional Genomics

scholarly journals Comparative Functional Genomics Analysis of NNK Tobacco-Carcinogen Induced Lung Adenocarcinoma Development in Gprc5a-Knockout Mice

PLoS ONE ◽  
2010 ◽  
Vol 5 (7) ◽  
pp. e11847 ◽  
Author(s):  
Junya Fujimoto ◽  
Humam Kadara ◽  
Taoyan Men ◽  
Carolyn van Pelt ◽  
Dafna Lotan ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Functional Genomics ◽  
Knockout Mice ◽  
Tobacco Carcinogen ◽  
Comparative Functional Genomics

scholarly journals Comparative functional genomics of adaptation to muscular disuse in hibernating mammals

2014 ◽  
Vol 23 (22) ◽  
pp. 5524-5537 ◽  
Author(s):  
Vadim B. Fedorov ◽  
Anna V. Goropashnaya ◽  
Nathan C. Stewart ◽  
Øivind Tøien ◽  
Celia Chang ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Comparative Functional Genomics

scholarly journals Comparative Functional Genomics of the Fission Yeasts

Science ◽  
2011 ◽  
Vol 332 (6032) ◽  
pp. 930-936 ◽  
Author(s):  
N. Rhind ◽  
Z. Chen ◽  
M. Yassour ◽  
D. A. Thompson ◽  
B. J. Haas ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Comparative Functional Genomics

Functional, structural and epitopic prediction of hypothetical proteins of Mycobacterium tuberculosis H37Rv: An in silico approach for prioritizing the targets

Gene ◽  
2016 ◽  
Vol 591 (2) ◽  
pp. 442-455 ◽  
Author(s):  
Md. Amran Gazi ◽  
Mohammad Golam Kibria ◽  
Mustafa Mahfuz ◽  
Md. Rezaul Islam ◽  
Prakash Ghosh ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
In Silico ◽  
Tuberculosis H37rv ◽  
Hypothetical Proteins ◽  
Mycobacterium Tuberculosis H37rv

scholarly journals Standardized genome-wide function prediction enables comparative functional genomics in plants: a new application area for Gene Ontologies

2021 ◽  
Author(s):  
Leila Fattel ◽  
Dennis Psaroudakis ◽  
Colleen F. Yanarella ◽  
Kevin Chiteri ◽  
Haley A. Dostalik ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Gene Function ◽  
Go Annotation ◽  
Functional Annotations ◽  
Genome Wide ◽  
Branch Support ◽  
Comparative Functional Genomics ◽  
Gene Ontologies ◽  
Established Species ◽  
Go Terms

BackgroundGenome-wide gene function annotations are useful for hypothesis generation and for prioritizing candidate genes responsible for phenotypes of interest. We functionally annotated the genes of 18 crop plant genomes across 14 species using the GOMAP pipeline.ResultsBy comparison to existing GO annotation datasets available for a subset of these genomes, GOMAP-generated datasets cover more genes, assign more GO terms, and produce datasets similar in quality (based on precision and recall metrics using existing gold standards as the basis for comparison). From there, we sought to determine whether the datasets could be used in tandem to carry out comparative functional genomics analyses. As a test of the idea and a proof of concept, we created parsimony and distance-based dendrograms of relatedness based on functions for all 18 genomes. These dendrograms were compared to well-established species-level phylogenies to determine whether trees derived through the analysis of gene function agree with known evolutionary histories, which they largely do. Where discrepancies were observed, we determined branch support based on jack-knifing then removed individual annotation sets by genome to identify the annotation sets causing errant relationships.ConclusionsBased on the results of these analyses, it is clear that for genome assembly and annotation products of similar quality, GOMAP-derived functional annotations used together across species do retain sufficient biological signal to recover known phylogenetic relationships, indicating that comparative functional genomics across species based on GO data hold promise as a tool for generating novel hypotheses about gene function and traits.

In Silico Drug Target Discovery Through Proteome Mining from M. tuberculosis: An Insight into Antivirulent Therapy

2020 ◽  
Vol 23 (3) ◽  
pp. 253-268
Author(s):  
Shreya Bhattacharya ◽  
Puja Ghosh ◽  
Debasmita Banerjee ◽  
Arundhati Banerjee ◽  
Sujay Ray
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Virulence Factors ◽  
Spectrum Analysis ◽  
Drug Target ◽  
Drug Targets ◽  
Physicochemical Characterization ◽  
Specific Drug ◽  
Hypothetical Proteins ◽  
Drug Target Discovery ◽  
Domain Annotation

Aim and Objective: One of the challenges to conventional therapies against Mycobacterium tuberculosis is the development of multi-drug resistant pathogenic strains. This study was undertaken to explore new therapeutic targets for the revolutionary antivirulence therapy utilizing the pathogen’s essential hypothetical proteins, serving as virulence factors, which is the essential first step in novel drug designing. Methods: Functional annotations of essential hypothetical proteins from Mycobacterium tuberculosis (H37Rv strain) were performed through domain annotation, Gene Ontology analysis, physicochemical characterization and prediction of subcellular localization. Virulence factors among the essential hypothetical proteins were predicted, among which pathogen-specific drug target candidates, non-homologous to human and gut microbiota, were identified. This was followed by druggability and spectrum analysis of the identified targets. Results and conclusion: The study successfully assigned functions of 83 essential hypothetical proteins of Mycobacterium tuberculosis, among which 25 were identified as virulence factors. Out of 25, 12 virulence factors were observed as potential pathogen-specific drug target candidates. Nine potential targets had druggable properties and rest three were considered as novel targets. Exploration of these targets will provide new insights into future drug development. Characterization of subcellular localizations revealed that most of the predicted targets were cytoplasmic which could be ideal for intracellular drugs, while two drug targets were membranebound, ideal for vaccines. Spectrum analysis identified one broad-spectrum and 11 narrowspectrum targets. This study would, therefore, instigate designing novel therapeutics for antivirulence therapy, which have the potential to serve as revolutionary treatment instead of conventional antibiotic therapies to overcome the lethality of antibiotic-resistant strains.

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