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We describe below some of the regulations we identified which have pharmaceutical relevance.
Human height is a complex heritable trait; by integrating genome-wide SNP data and human adipose Bayesian causal network, which closely represents bone transcriptional regulations, we identified PLAG1 as a causal gene for limb bone length.
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For nuclear regulation, we identified two up-regulated high mobility group genes as well as several up-regulated transcriptional regulators including polyhomeotic-like and PalB-like genes.
In the course of our studies on compartment-specific lipid-mediated cell regulation, we identified an intimate connection between ceramides (Cers) and the mitochondria-dependent death-signaling pathways.
Among 846 human genes with putative roles in cell cycle regulation, we identified 46 transcription factors and 39 gene ontology groups.
Coupling these three components of measuring transcriptional regulation, we identified in the human P493-6 B cell model, a set of direct Myc targets that are involved in ribosomal biogenesis, nucleotide metabolism, energy metabolism and cell cycle progression.
Using a fold-change threshold of 2 (up-regulation) and 2 (down-regulation), we identified 971 deregulated genes after combined masitinib plus gemcitabine treatment (845 up- and 126 down-regulated); 1161 deregulated genes after gemcitabine monotherapy (1048 up- and 113 down-regulated); and only 354 deregulated genes after masitinib monotherapy (325 up- and 29 down-regulated).
Focusing on genes involved in transcriptional regulation, we identified transcripts annotated as likely transcription factors (TFs) in Table 2.
In order to explore the mechanism of KLK15 gene regulation, we identified the promoter of this gene by aligning its genomic sequence against the Human Genome Project sequence database.
Incorporating the optimal conditions of ceRNA regulation, we identified the optimal ceRNA pairs and revealed the biological functions significantly associated with protein transport, protein catabolic processes, and regulation of translation.
By comparative SVD approach, followed by Bayesian network analysis of cis-regulation, we identified two conserved eigensystems separating the effects of different well-defined biological processes on gene expression and regulated by distinct sets of transcription factor binding sites.
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