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Monodomain proteins with an apparent function were considered annotated unless manual inspection revealed the domain to be either pending true annotation or associated with a large variety of activities that prevented the inference of a precise function.
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First and most importantly, cross-sectional data were collected, preventing the inference of causal relationships.
First, the cross-sectional nature of the data poses a limitation and prevents the inference of causal relationships.
Numerous approaches exist for modeling of genetic regulatory networks (GRNs) but the low sampling rates often employed in biological studies prevents the inference of detailed models from experimental data.
Such an approach laboriously requires the creation of an entirely new set of assertions, and there may be recursion in that the more basic object terms may not exist in a hierarchical relationship, thus once again preventing the inference of the is_a link between the more composite subject terms.
In this paper, we propose Sensor Guardian, a new system to prevent the problem of privacy inference based on sensors (PIS).
This allowed the identification of novel biomarkers, but the protein identification limitation of the SELDI-TOF technique prevented mechanistic inference and predictions [ 35].
This also prevented statistical inference using bootstrapped trees, and the topology from the Bayesian phylogeny was limited by several polytomies (supplementary fig. S2 B, Supplementary Material online).
Overall the cross-sectional design prevented any inference as to causality.
Unfortunately, the low resolution of the recent structure of the apoptosome obtained by cryo-EM prevented any inference regarding intermolecular contacts involving cytochrome c [29], [30].
Moreover, the approximate inference result will prevent the marginal likelihood from being optimized efficiently, due to the fact that we cannot evaluate the objective value correctly.
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