Munging for deeper meaning in nanotoxicologic studies with select model-driven discovery, cleaner nano-ontolytics, and tightly-targeted in silico text queries
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ABSTRACT:
Unlike other emergent but comparatively better-established sub-fields within the nanosciences, the nascent disciplines of nano-toxicology and nano-pathology are dense harvesting fields of ‘unknown unknowns’, yielding tangled thickets of lurking variables and complex, uncontrolled-for confounding factors.
The roots of data detritus in nanorisk studies stem from malformed morphologies propagated through labs, germinating throughout research repositories, requiring anatomic, systemic weeding-out of invasively procreative, inaptly-introduced terminologies. So deeply embedded throughout library databases and institutional depositories is ill-structured nanotox nomenclature that its semantic offshoots choke off and threaten organic development of nano-’s broader landscape.
With a view towards semantic clarity engendering speed, precision, and protocol harmonization, the DeepMed Library devised a single-access-point, data-detritus-reduction mechanism as a nano-knowledge-discovery tool crafted to resolve noisy nano-ontolytics within computational nanotoxicology.
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