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Circular chromosome conformation capture, when coupled with next-generation sequencing (4C-Seq), can be used to identify genome-wide interaction of a given locus (a "bait" sequence) with all of its interacting partners.
Strikingly, the node strength grows super-linearly with the degree, i.e., the cumulated time of interaction of a given individual grows super-linearly with the number of distinct persons that this individual has had contacts with.
Therefore each visit can be considered as a unique courtship interaction of a given male-female pair.
Within the interactome of S. cerevisiae, the first interaction of a given protein increases its rate of gaining a new one by approximately 100%.
A critical prerequisite to study the interaction of a given immune cell subset with the spinal cord microvasculature using the IVM method described here, is to obtain a highly purified population of the cells of interest.
Unlike most other predictors, the method by Chen et al. operates on the atomic level, utilizing PDMs (encoding the probabilistic "strength" of interaction of a given protein atom with every other potential atom type) to produce atom-level feature vectors [ 7].
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Although different types of interactions on a given target might correspond to different binding sites, it is theoretically possible for a non-linear classifier like SVM with non-linear kernels to learn classes consisting of several disconnected sets.
The prior odds quantifies the chance of interaction for a given TF target pair when all pairs are considered and can be defined as P(B=1)/ P(B=0), where P(B=1) is the probability of a physical interaction.
We sometimes identify just one such pattern of target interaction for a given activity or, on other occasions, find distinct sets of targets whose modulation is associated with the same function.
Due to the dependence of ChemDIS on chemical protein interactions, the number of interactions for a given chemical determines its applicability domain.
One of the approaches is to limit the number of interactions for a given gene [ 5, 8].
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CEO of Professional Science Editing for Scientists @ prosciediting.com