Mission of randomness

Zhou, Guo-Ping

doi:10.4161/viru.27136

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…2 Investigation of these candidates and other biological problems using experimental methods are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Therefore, many studies from various research laboratories around the world have indicated that mathematical analysis, computational modeling, and the introduction of novel physical concepts to solve important problems in biology and medicine, (such as random walk models, 3,4 protein-protein interaction network, [5][6][7][8][9] protein structural class prediction, 10,11 modeling 3D structures of targeted proteins for drug design, [12][13][14][15] diffusion-controlled reaction simulation, [16][17][18][19] cellular responding kinetics, 20 bio-macromolecular internal collective motion simulation, [21][22][23] identification of proteases and their types, 24 membrane protein type prediction, 25 protein cleavage site prediction, 26,27 and signal peptide prediction, 28 ) can provide very useful information and insights for basic research and hence are widely welcomed by the scientific community. The present study is related to the fundamental problems in systems biology, network biology, and the structural biology of proteins.…”

Section: Introductionmentioning

confidence: 99%

Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression

et al. 2014

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The identification of disease genes is very important not only to provide greater understanding of gene function and cellular mechanisms which drive human disease, but also to enhance human disease diagnosis and treatment. Recently, high-throughput techniques have been applied to detect dozens or even hundreds of candidate genes. However, experimental approaches to validate the many candidates are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Therefore, numerous theoretical and computational methods (e.g. network-based approaches) have been developed to prioritize candidate disease genes. Many network-based approaches implicitly utilize the observation that genes causing the same or similar diseases tend to correlate with each other in gene-protein relationship networks. Of these network approaches, the random walk with restart algorithm (RWR) is considered to be a state-of-the-art approach. To further improve the performance of RWR, we propose a novel method named ESFSC to identify disease-related genes, by enlarging the seed set according to the centrality of disease genes in a network and fusing information of the protein-protein interaction (PPI) network topological similarity and the gene expression correlation. The ESFSC algorithm restarts at all of the nodes in the seed set consisting of the known disease genes and their k-nearest neighbor nodes, then walks in the global network separately guided by the similarity transition matrix constructed with PPI network topological similarity properties and the correlational transition matrix constructed with the gene expression profiles. As a result, all the genes in the network are ranked by weighted fusing the above results of the RWR guided by two types of transition matrices. Comprehensive simulation results of the 10 diseases with 97 known disease genes collected from the Online Mendelian Inheritance in Man (OMIM) database show that ESFSC outperforms existing methods for prioritizing candidate disease genes. The top prediction results of Alzheimer's disease are consistent with previous literature reports.

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Section: Introductionmentioning

confidence: 99%

Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression

et al. 2014

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Towards In Silico 3-D Structure Modeling and Prioritization of Candidate Genes Regulating the Bovine and Caprine Apelinergic System

Gogoi

Kuri

Karunakaran

et al. 2023

Preprint

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Background The Apelinergic system (consisting of two ligands - APELIN/APELA and its receptor APJ) plays a crucial role in many important biological processes in animals. The human Apelin, Apela and its receptor APJ are well characterized in terms of structure and function, but very little is known about the two ligands and its receptor in bovines and caprine species. The genes related to the Apelinergic system and their roles in various metabolic processes are also understudied in terms of livestock such as bovine and caprine species. Therefore, the aims of the present were to a) model the 3-D structure of the Apelinergic system and b) identify and prioritize the candidate genes regulating the system in bovine and caprine species through state of art bioinformatics tools. A three-dimensional model (3D) was constructed using SWISS-Model, a homology modeling server. The predicted model was validated by SAVES including PROCHECK and ERRAT server. The structures were refined by Refold server of intfold homology modeling tool. Python molecular viewer (PyMol) was used to visualize the tertiary structure of the protein. Three gene prioritizing tools Genie, toppgenet, David, and Genemania to further visualize the network of genes were used.Results The overall quality factor for the remodeled 3D structure for the three best templates selected for both bovine and caprine species was found to be 97.95, 97.82 and 96.40%. We identified and prioritized the top 10 most important genes related to each of the ligands (Apelin/apela and their receptor APJ) and the top 20 neighboring genes for both bovine and caprine species. The top 10 most common genes that interacted with the Apelinergic system in bovines and caprines are FLT1, ADIPOR1, ADIPOR2, ADIPOQ, INS, LEP, KDR, AKT1, TGFB1, NOS3, EGFR1, IGFR1, VEGFA, EGFR, FGF2, MAPK1/3, PPARG, PPARD, and APLNR.Conclusion The models generated in the present study can be used as a foundation for future drug-designing strategies and experiments. The result of the study may be a guiding point for further investigations on the role of the Apelinergic system in various physiological processes in bovines and caprine species.

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Metabolism of Oxalate in Humans: A Potential Role Kynurenine Aminotransferase/Glutamine Transaminase/Cysteine Conjugate Betalyase Plays in Hyperoxaluria

Han

Yang

et al. 2019

CMC

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Hyperoxaluria, excessive urinary oxalate excretion, is a significant health problem worldwide. Disrupted oxalate metabolism has been implicated in hyperoxaluria and accordingly, an enzymatic disturbance in oxalate biosynthesis can result in the primary hyperoxaluria. Alanine-glyoxylate aminotransferase-1 and glyoxylate reductase, the enzymes involving glyoxylate (precursor for oxalate) metabolism, have been related to primary hyperoxalurias. Some studies suggest that other enzymes such as glycolate oxidase and alanine-glyoxylate aminotransferase-2 might be associated with primary hyperoxaluria as well, but evidence of a definitive link is not strong between the clinical cases and gene mutations. There are still some idiopathic hyperoxalurias, which require a further study for the etiologies. Some aminotransferases, particularly kynurenine aminotransferases, can convert glyoxylate to glycine. Based on biochemical and structural characteristics, expression level, and subcellular localization of some aminotransferases, a number of them appear able to catalyze the transamination of glyoxylate to glycine more efficiently than alanine glyoxylate aminotransferase-1. The aim of this minireview is to explore other undermining causes of primary hyperoxaluria and stimulate research toward achieving a comprehensive understanding of underlying mechanisms leading to the disease. Herein, we reviewed all aminotransferases in the liver for their functions in glyoxylate metabolism. Particularly, kynurenine aminotransferase-I and III were carefully discussed regarding their biochemical and structural characteristics, cellular localization, and enzyme inhibition. Kynurenine aminotransferase-III is, so far, the most efficient putative mitochondrial enzyme to transaminate glyoxylate to glycine in mammalian livers, which might be an interesting enzyme to look for in hyperoxaluria etiology of primary hyperoxaluria and should be carefully investigated for its involvement in oxalate metabolism.

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Mission of randomness

Cited by 4 publications

References 16 publications

Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression

Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression

Towards In Silico 3-D Structure Modeling and Prioritization of Candidate Genes Regulating the Bovine and Caprine Apelinergic System

Metabolism of Oxalate in Humans: A Potential Role Kynurenine Aminotransferase/Glutamine Transaminase/Cysteine Conjugate Betalyase Plays in Hyperoxaluria

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