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Results for “schema matching”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Nonparametric Bayesian Modeling for Automated Database Schema Matching

The problem of merging databases arises in many government and commercial applications. Schema matching, a common first step, identifies equivalent fields between databases. We introduce a schema matching framework that builds nonparametric Bayesian models for each field and compares them by computing the probability that a single model could have generated both fields. Our experiments show that our method is more accurate and faster than the existing instance-based matching algorithms in part because of the use of nonparametric Bayesian models.

Bayesian↗

Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning

Abstract Motivation Creating knowledge bases and ontologies is a time consuming task that relies on manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not able to populate arbitrarily complex nested knowledge schemas. Results Here we present Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES), a Knowledge Extraction approach that relies on the ability of Large Language Models (LLMs) to perform zero-shot learning and general-purpose query answering from flexible prompts and return information conforming to a specified schema. Given a detailed, user-defined knowledge schema and an input text, SPIRES recursively performs prompt interrogation against an LLM to obtain a set of responses matching the provided schema. SPIRES uses existing ontologies and vocabularies to provide identifiers for matched elements. We present examples of applying SPIRES in different domains, including extraction of food recipes, multi-species cellular signaling pathways, disease treatments, multi-step drug mechanisms, and chemical to disease relationships. Current SPIRES accuracy is comparable to the mid-range of existing Relation Extraction methods, but greatly surpasses an LLM’s native capability of grounding entities with unique identifiers. SPIRES has the advantage of easy customization, flexibility, and, crucially, the ability to perform new tasks in the absence of any new training data. This method supports a general strategy of leveraging the language interpreting capabilities of LLMs to assemble knowledge bases, assisting manual knowledge curation and acquisition while supporting validation with publicly-available databases and ontologies external to the LLM. Availability and implementation SPIRES is available as part of the open source OntoGPT package: https://github.com/monarch-initiative/ontogpt.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WCB001

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNV-NY99 382) and mutant WNV-E218A virus infection. Sample data was obtained from mouse cerebellum tissue and processed for mRNA, miRNA, proteomics, metabolomics, and lipidomics expression analysis. Tissues from this experiment were matched to tissues from GSE77193 (WCT001), using 1/4 of the cortex and 1/2 of cerebellum from the same mice. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Omics-Lethal Human Viruses, West Nile Experiment WCT001

The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNV-NY99 382) and mutant WNV-E218A (WNV-NY99 382 E218A 2 nt) virus infection. Sample data was obtained from mouse cortex tissue for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Tissues from this experiment were matched to tissues from GSE77192 (WCB001), using 1/4 of the cortex and 1/2 of cerebellum from the same mice. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative impact of changes in marrow cellularity, skeletal size, and bone mineral density on active marrow dosimetry based upon a reference model

Purpose The hematopoietically active tissues of skeletal bone marrow are a prime target for computational dosimetry given potential risks of leukemia and, at higher dose levels, acute marrow toxicity. The complex three‐dimensional geometry of trabecular spongiosa, however, complicates schema for dose assessment in such a way that only a few reference skeletal models have been developed to date, and which are based upon microimaging of a limited number of cadaveric bone spongiosa cores. The question then arises as to what degree of accuracy is achievable from reference skeletal dose models when applied to individual patients or specific exposed populations? Methods Patient variability in marrow dosimetry were quantified for three skeletal sites — the ribs, lumbar vertebrae, and cranium — for the beta‐emitters 45 Ca, 153 Sm, and 90 Y, and the alpha‐particle emitters 223 Ra, 219 Rn, and 215 Po, the latter two being the immediate progeny of the former. For each radionuclide and bone site, three patient parameters were altered from their values in the reference model: (1) bone size as a surrogate for patient stature, (2) marrow cellularity as a surrogate for age‐ or disease‐related changes in marrow adiposity, and (3) the trabecular bone volume fraction as a surrogate for bone mineral density. Marrow dose variability is expressed as percent differences in the radionuclide S value given by the reference model and the patient‐parameterized model. The impact of radionuclide biokinetics on marrow dosimetry was not considered. Results Variations in overall bone size play a very minor role in active marrow dose variability. Marrow cellularity is a significant factor in dose variability for active marrow self‐irradiation, but it plays no role for radionuclides localized to the trabecular bone matrix. Variations in trabecular bone volume fractions impact the active marrow dose variability for short‐range particle emitters 45 Ca, 223 Ra, 219 Rn, and 215 Po in the vertebrae and ribs, skeletal sites with small spongiosa proportions of trabecular bone. In the cranium, with its relative high proportion of trabecular bone, significant differences in marrow dosimetry from the reference model were noted for all radionuclides. Conclusions Skeletal models of active marrow dosimetry should be more fully parameterized to permit closer matching to patient bone density and marrow cellularity, particularly when considering short‐range particle emitters localized to either the bone trabeculae or active marrow, respectively.

Geyer, Amy M.↗