scholarly journals Protein Interaction Verification and Functional Annotation by Integrated Analysis of Genome-Scale Data

2002 ◽  
Vol 9 (5) ◽  
pp. 1133-1143 ◽  
Author(s):  
Patrick Kemmeren ◽  
Nynke L. van Berkum ◽  
Jaak Vilo ◽  
Theo Bijma ◽  
Rogier Donders ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Functional Annotation ◽  
Integrated Analysis ◽  
Genome Scale ◽  
Scale Data

scholarly journals Genome-Scale Data Call for a Taxonomic Rearrangement of Geodermatophilaceae

2017 ◽  
Vol 8 ◽  
Author(s):  
Maria del Carmen Montero-Calasanz ◽  
Jan P. Meier-Kolthoff ◽  
Dao-Feng Zhang ◽  
Adnan Yaramis ◽  
Manfred Rohde ◽  
...  
Keyword(s):  
Genome Scale ◽  
Data Call ◽  
Scale Data

scholarly journals A genome-scale protein interaction profile of Drosophila p53 uncovers additional nodes of the human p53 network

2010 ◽  
Vol 107 (14) ◽  
pp. 6322-6327 ◽  
Author(s):  
A. Lunardi ◽  
G. Di Minin ◽  
P. Provero ◽  
M. Dal Ferro ◽  
M. Carotti ◽  
...  
Keyword(s):  
Protein Interaction ◽  
A Genome ◽  
Genome Scale ◽  
P53 Network

Proteomic analysis of the colistin-resistant E. coli clinical isolate: Explorations of the resistome

2021 ◽  
Vol 28 ◽  
Author(s):  
Divakar Sharma ◽  
Manisha Aswal ◽  
Nayeem Ahmad ◽  
Manish Kumar ◽  
Asad U Khan
Keyword(s):  
Clinical Isolate ◽  
Protein Interaction ◽  
Functional Annotation ◽  
Drug Targets ◽  
Bacterial Infections ◽  
Sugar Metabolism ◽  
Colistin Resistance ◽  
Phosphotransferase System ◽  
E Coli ◽  
Protein Protein Interaction

Background: Antimicrobial resistance is a worldwide problem after the emergence of colistin resistance since it was the last option left to treat carbapenemase-resistant bacterial infections. The mcr gene and its variants are one of the causes for colistin resistance. Besides mcr genes, some other intrinsic genes are also involved in colistin resistance but still need to be explored. Objective: The aim of this study was to investigate differential proteins expression of colistin-resistant E. coli clinical isolate and to understand their interactive partners as future drug targets. Methods: In this study, we have employed the whole proteome analysis through LC-MS/MS. The advance proteomics tools were used to find differentially expressed proteins in the colistin-resistant Escherichia coli clinical isolate compared to susceptible isolate. Gene ontology and STRING were used for functional annotation and protein-protein interaction networks, respectively. Results: LC-MS/MS analysis showed overexpression of 47 proteins and underexpression of 74 proteins in colistin-resistant E. coli. These proteins belong to DNA replication, transcription and translational process; defense and stress related proteins; proteins of phosphoenol pyruvate phosphotransferase system (PTS) and sugar metabolism. Functional annotation and protein-protein interaction showed translational and cellular metabolic process, sugar metabolism and metabolite interconversion. Conclusion: We conclude that these protein targets and their pathways might be used to develop novel therapeutics against colistin-resistant infections. These proteins could unveil the mechanism of colistin resistance.

scholarly journals CausalR: extracting mechanistic sense from genome scale data

2017 ◽  
Vol 33 (22) ◽  
pp. 3670-3672 ◽  
Author(s):  
Glyn Bradley ◽  
Steven J Barrett
Keyword(s):  
Genome Scale ◽  
Scale Data

scholarly journals Using target enrichment sequencing to study the higher-level phylogeny of the largest lichen-forming fungi family: Parmeliaceae (Ascomycota)

IMA Fungus ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Felix Grewe ◽  
Claudio Ametrano ◽  
Todd J. Widhelm ◽  
Steven Leavitt ◽  
Isabel Distefano ◽  
...  
Keyword(s):  
Data Sets ◽  
Target Enrichment ◽  
Data Set ◽  
Reduced Genome ◽  
Genome Data ◽  
Worldwide Distribution ◽  
Phylogenetic Studies ◽  
Genome Scale ◽  
Scale Data ◽  
Promising Avenue

AbstractParmeliaceae is the largest family of lichen-forming fungi with a worldwide distribution. We used a target enrichment data set and a qualitative selection method for 250 out of 350 genes to infer the phylogeny of the major clades in this family including 81 taxa, with both subfamilies and all seven major clades previously recognized in the subfamily Parmelioideae. The reduced genome-scale data set was analyzed using concatenated-based Bayesian inference and two different Maximum Likelihood analyses, and a coalescent-based species tree method. The resulting topology was strongly supported with the majority of nodes being fully supported in all three concatenated-based analyses. The two subfamilies and each of the seven major clades in Parmelioideae were strongly supported as monophyletic. In addition, most backbone relationships in the topology were recovered with high nodal support. The genus Parmotrema was found to be polyphyletic and consequently, it is suggested to accept the genus Crespoa to accommodate the species previously placed in Parmotrema subgen. Crespoa. This study demonstrates the power of reduced genome-scale data sets to resolve phylogenetic relationships with high support. Due to lower costs, target enrichment methods provide a promising avenue for phylogenetic studies including larger taxonomic/specimen sampling than whole genome data would allow.

scholarly journals Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

PLoS ONE ◽  
2013 ◽  
Vol 8 (1) ◽  
pp. e53930 ◽  
Author(s):  
Julia Salzman ◽  
Daniel M. Klass ◽  
Patrick O. Brown
Keyword(s):  
Molecular Interactions ◽  
Adaptive Model ◽  
Model Based ◽  
Genome Scale ◽  
Scale Data
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