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Impairment of DNA Methylation Maintenance Is the Main Cause of Global Demethylation in Naive Embryonic Stem Cells
In Brief Global demethylation during epigenetic reprogramming in preimplantation embryos, primordial germ cells, and naive embryonic stem cells is a consequence of impaired DNA methylationExpand
Impairment of DNA Methylation Maintenance Is the Main Cause of Global Demethylation in Naive Embryonic Stem Cells
TLDR
The observations establish the molecular mechanism for global demethylation in naive ESCs, which has key parallels with those operating in primordial germ cells and early embryos. Expand
Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation.
TLDR
Results show that regardless of significant up- and down-regulated metabolic genes, the distribution of metabolic changes is similar in different cancer types, which supports the theory that the Warburg effect is a consequence of metabolic adaptation in cancer cells. Expand
Controllability in Cancer Metabolic Networks According to Drug Targets as Driver Nodes
TLDR
This study reveals the possibilities of following a set of driver nodes in network clusters instead of considering them individually according to their centralities, leading to a new strategy in the field of network medicine. Expand
CytoKavosh: A Cytoscape Plug-In for Finding Network Motifs in Large Biological Networks
TLDR
For the first time, CytoKavosh is introduced as the first plug-in of its kind, which supports us in finding motifs of given size in a network that is formerly loaded into the Cytoscape work-space (directed or undirected). Expand
CentiServer: A Comprehensive Resource, Web-Based Application and R Package for Centrality Analysis
TLDR
The newly created CentiServer is a comprehensive online resource that provides over 110 definitions of different centrality indices, their computational methods, and algorithms in the form of an encyclopedia. Expand
HomoTarget: a new algorithm for prediction of microRNA targets in Homo sapiens.
TLDR
Combined pattern recognition neural network (PRNN) and principle component analysis (PCA) architecture has been proposed in order to model the complicated relationship between miRNAs and their target mRNAs in humans. Expand
Computational Analysis of Reciprocal Association of Metabolism and Epigenetics in the Budding Yeast: A Genome-Scale Metabolic Model (GSMM) Approach
TLDR
Centrality analysis shows that the lowly expressed enzymes could affect and control the yeast metabolic network and constraint-based modeling results are in a good agreement with the experimental findings, confirming that the mutations in histone tails lead to non-lethal alterations in the yeast, but have diverse effects on the growth rate and reveal the functional redundancy. Expand
Meta-Analysis of Gene Expression Profiles in Acute Promyelocytic Leukemia Reveals Involved Pathways
TLDR
A meta-analysis of gene expression profiles derived from microarray experiments revealed a gene signature with 406 genes that are up or down-regulated in APL and determined that MAPK pathway and its involved elements such as JUN gene and AP-1 play important roles inAPL pathogenesis along with insulin-like growth factor–binding protein-7. Expand
A systematic survey of centrality measures for protein-protein interaction networks
TLDR
It is concluded that undertaking data reduction using unsupervised machine learning methods helps to choose appropriate variables (centrality measures) and identify the contribution proportions of the centrality measures with PCA as a prerequisite step of network analysis before inferring functional consequences, e.g., essentiality of a node. Expand
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