Is the average shortest path length of gene set a reflection of their biological relatedness?

Embar, Varsha; Handen, Adam; Ganapathiraju, Madhavi K.

doi:10.1142/s0219720016600027

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…The value of the diameter in the primary and subnetwork were 38 and 28, respectively. Embar et al (2016) reported the path length is of biological interest because it is assumed that a functionally related gene would be more closely connected in the metabolome in a gene network [31]. The average path length presents a measure of the network's overall navigability and it is assumed that functionally related genes would be more closely connected in the metabolome that the value in the primary and subnetwork which were equal to 13.142 and 6.913, respectively.…”

Section: Acidosis Metabolic Networkmentioning

confidence: 99%

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

Gholizadeh

Fayazi

Asgari

et al. 2020

Animals

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The objective of this study was to develop a system-level understanding of acidosis biology. Therefore, the genes expression differences between the normal and acidosis rumen epithelial tissues were first examined using the RNA-seq data in order to understand the molecular mechanisms involved in the disease and then their corresponding metabolic networks constructed. A number of 1074 genes, 978 isoforms, 1049 transcription start sites (TSS), 998 coding DNA sequence (CDS) and 2 promoters were identified being differentially expressed in the rumen tissue between the normal and acidosis samples (p < 0.05). The functional analysis of 627 up-regulated genes revealed their involvement in ion transmembrane transport, filament organization, regulation of cell adhesion, regulation of the actin cytoskeleton, ATP binding, glucose transmembrane transporter activity, carbohydrate binding, growth factor binding and cAMP metabolic process. Additionally, 111 differentially expressed enzymes were identified between the rumen epithelial tissue of the normal and acidosis steers with 46 up-regulated and 65 down-regulated ones in the acidosis group. The pathways and reactions analyses associated with the up-regulated enzymes indicate that most of these enzymes are involved in the fatty acid metabolism, biosynthesis of amino acids, pyruvate and carbon metabolism while most of the down-regulated ones are involved in purine and pyrimidine, vitamin B6 and antibiotics metabolisms. The degree distribution of both metabolic networks follows a power-law one, hence displaying a scale-free property. The top 15 hub metabolites were determined in the acidosis metabolic network with most of them involved in the fatty acid oxidation, VFA biosynthesis, amino acid biogenesis and glutathione metabolism which plays an important role in the stress condition. The limitations of this study were low number of animals and using only epithelial tissue (ventral sac) for RNA-seq.

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Section: Acidosis Metabolic Networkmentioning

confidence: 99%

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

Gholizadeh

Fayazi

Asgari

et al. 2020

Animals

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“…The average distance between genes has been proposed as a proxy for functional relatedness. However, some studies have shown that the average shortest path length between genes associated with a specific disease is imposed by the degree of the chosen genes and it is independent of their function (Embar et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk

2020

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Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated biomolecular processes. Second, metabolism is characterized by a high degree of stability reflected by the organisms resilience to either environmental changes or pathogenic conditions. Here we will investigate the relationship between these two features. By having access to the full set of human metabolic interactions as reported in the highly curated KEGG database, we built an integrated human metabolic network comprising metabolic, transcriptional regulation, and protein-protein interaction networks. We hypothesized that a metabolic process may exhibit resilience if it can recover from perturbations at the pathway level; in other words, metabolic resilience could be due to pathway crosstalk which may implicate that a metabolic process could proceed even when a perturbation has occurred. By analyzing the topological structure of the integrated network, as well as the hierarchical structure of its main modules or subnetworks, we observed that behind biological resilience lies an intricate communication structure at the topological and functional level with pathway crosstalk as the main component. The present findings, alongside the advent of large biomolecular databases, such as KEGG may allow the study of the consequences of this redundancy and resilience for the study of healthy and pathological phenotypes with many potential applications in biomedical science.

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“…As evident from the plot (Figure 7B), the distribution of shortest paths between all nodes in random networks was significantly larger than those of shortest paths in the native network. This indicated dense connectivity and therefore functional cohesiveness among network proteins since functionally related genes reside closer to each other within the interaction network (Embar, Handen, & Ganapathiraju, 2016) for quick information transfer. While various NiV host factor proteins are identified by Martinez-Gil et al (2017) (Martinez-Gil et al, 2017, two of these PON2 (Paraoxonase 2) and GPX1 (Glutathione peroxidase) were found to be most important connecting links between host and viral interaction networks during our analysis.…”

Section: Network-based Correlation Among Interaction Network Componentsmentioning

confidence: 95%

Identifying potential entry inhibitors for emerging Nipah virus by molecular docking and chemical-protein interaction network

Pathania

Randhawa

Kumar

2019

Journal of Biomolecular Structure and Dynamics

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Nipah Virus (NiV) is a newly emergent paramyxovirus that has caused various outbreaks in Asian countries. Despite its acute pathogenicity and lack of approved therapeutics for human use, there is an urgent need to determine inhibitors against NiV. Hence, this work includes prospection of potential entry inhibitors by implementing an integrative structure-and network-based drug discovery approach. FDA-approved drugs were screened against attachment glycoprotein (NiV-G, PDB: 2VSM), one of the prime targets to inhibit viral entry, using a molecular docking approach that was benchmarked both on CCDC/ASTEX and known NIV-G inhibitor set. The predicted small molecules were prioritized on the basis of topological analysis of the chemical-protein interaction network, which was inferred by integrating the drug-target network, NiV-human interaction network, and human proteinprotein interaction network. A total of 17 drugs were predicted to be NiV-G inhibitors using molecular docking studies that were further prioritized to 3 novel leads À Nilotinib, Deslanoside and Acetyldigitoxin À on the basis of topological analysis of inferred chemical-protein interaction network. While Deslanoside and Acetyldigitoxin belong to an already known class of anti-NiV inhibitors, Nilotinib belongs to Benzenoids chemical class that has not been reported hitherto for developing anti-NiV inhibitors. These identified drugs are expected to be successful in further experimental evaluation and therefore could be used for anti-Nipah drug discovery. Apart, we also obtained various insights into the underlying chemical-protein interaction network, based on which several important network nodes were predicted. The applicability of our proposed approach was also demonstrated by prospecting for anti-NiV phytochemicals on an independent dataset.

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Is the average shortest path length of gene set a reflection of their biological relatedness?

Cited by 13 publications

References 20 publications

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk

Identifying potential entry inhibitors for emerging Nipah virus by molecular docking and chemical-protein interaction network

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