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To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network DRINN).
In order to identify molecules that function downstream of Fz2 for development of the adult flight circuit, interactions of candidate genes were tested.
In order to motivate our approach, we evaluate here the performance of random walk with restarts and network propagation with respect to the network degree (number of known interactions) of candidate genes.
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Cytoscape_V2.6.3 software was used to investigate the interaction of candidate genes that were observed from the single and epistatic QTL results and the gene interaction network was constructed.
Thermodynamic and physico-chemical descriptors play a crucial role in the interaction of candidate compounds with their specific receptors (eg, biological membrane).
Ongoing projects include epidemiologic and clinical investigations of risk factors and the development of animal and cellular models to examine the interaction of candidate neurotoxicants with signaling pathways and molecules that have been implicated in autism.
The potential pathway for fatty acid synthesis in B. napus, which included 50 genes and the five regulatory factors mentioned above, was constructed by combining the main pathways that involved interaction of candidate genes as well as knowledge of fatty acid regulatory pathways in Arabidopsis.
The regulatory pathway constructed in this study was based on QTL information and the interaction of candidate genes associated with the single and epistatic QTLs of 10 fatty acids, as well as previous knowledge concerning Brassica species and Arabidopsis [ 31, 42].
The compounds displaying high docking score were visually prioritized to identify the best-fitting compounds, i. e. the ones which adequately mimic the interactions of clinical candidate inhibitor Nutlin-3a.
The second technique considers the dynamic changes in interactions of the candidate gene with other genes in the compared samples (normal and disease samples), which has been done by defining hubs from a protein-protein interaction network (PPIN) and checking if the hub and its neighbors are co-expressed together in different tissues [15].
With two unsupervised algorithms, principal component analysis and graphical Gaussian models, putative interactions of the candidate genes were determined and reconstructed by literature mining.
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