Repeat-dose toxicity prediction with Generalized Read-Across (GenRA) using targeted transcriptomic data: A proof-of-concept case study

AbstractPurposeThis paper compares the paradigmatic differences between knowledge organization (KO) in library and information science and knowledge representation (KR) in AI to show the convergence in KO and KR methods and applications.MethodologyThe literature review and comparative analysis of KO and KR paradigms is the primary method used in this paper.FindingsA key difference between KO and KR lays in the purpose of KO is to organize knowledge into certain structure for standardizing and/or normalizing the vocabulary of concepts and relations, while KR is problem-solving oriented. Differences between KO and KR are discussed based on the goal, methods, and functions.Research limitationsThis is only a preliminary research with a case study as proof of concept.Practical implicationsThe paper articulates on the opportunities in applying KR and other AI methods and techniques to enhance the functions of KO.Originality/value:Ontologies and linked data as the evidence of the convergence of KO and KR paradigms provide theoretical and methodological support to innovate KO in the AI era.

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Vitis OneGenE: A Causality-Based Approach to Generate Gene Networks in Vitis vinifera Sheds Light on the Laccase and Dirigent Gene Families

Biomolecules ◽

10.3390/biom11121744 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1744

Author(s):

Stefania Pilati ◽

Giulia Malacarne ◽

David Navarro-Payá ◽

Gabriele Tomè ◽

Laura Riscica ◽

...

Keyword(s):

Gene Networks ◽

Functional Characterization ◽

Gene Families ◽

Stilbene Synthase ◽

Breeding Programs ◽

Transcriptomic Data ◽

Network Analyses ◽

Manual Curation ◽

Inference Methods

The abundance of transcriptomic data and the development of causal inference methods have paved the way for gene network analyses in grapevine. Vitis OneGenE is a transcriptomic data mining tool that finds direct correlations between genes, thus producing association networks. As a proof of concept, the stilbene synthase gene regulatory network obtained with OneGenE has been compared with published co-expression analysis and experimental data, including cistrome data for MYB stilbenoid regulators. As a case study, the two secondary metabolism pathways of stilbenoids and lignin synthesis were explored. Several isoforms of laccase, peroxidase, and dirigent protein genes, putatively involved in the final oxidative oligomerization steps, were identified as specifically belonging to either one of these pathways. Manual curation of the predicted sequences exploiting the last available genome assembly, and the integration of phylogenetic and OneGenE analyses, identified a group of laccases exclusively present in grapevine and related to stilbenoids. Here we show how network analysis by OneGenE can accelerate knowledge discovery by suggesting new candidates for functional characterization and application in breeding programs.

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THE DIGITAL RESTITUTION OF LOT 3317: USING UNDERWATER IMAGE BASED MODELLING TO GENERATE VALUE IN VIRTUAL HERITAGE EXPERIENCES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w15-1163-2019 ◽

2019 ◽

Vol XLII-2/W15 ◽

pp. 1163-1170

Author(s):

K. T. D. Tousant ◽

S. Fai

Keyword(s):

Cultural Values ◽

Spatial Dynamics ◽

Cultural Value ◽

Proof Of Concept ◽

Cultural Resource ◽

Head Mounted Display ◽

Virtual Heritage ◽

Underwater Image ◽

History Of

<p><strong>Abstract.</strong> The intent of this paper is to demonstrate the cultural value that Virtual Heritage experiences can generate. As a proof of concept, game resolution assets were optimized from high polygon image based models (IBMs) and rendered in real-time, within a Head Mounted Display (HMD). The case study of lot 3317 was chosen to facilitate heuristic explorations pertinent to the history of the St. Lawrence Seaway, Canada. This case study explores methods in creating and validating heritage values, while valourizing assets as a cultural resource for use in the future. While at the same time, challenging the current spatial dynamics by conceptually reducing the distance between the viewer and the flooded landscape. In addition to demonstrating the cultural values generated through the veneration of lot 3317, the paper aims to provide a model for optimizing and post processing meshes produced through Under-Water Image-Base Modelling.</p>

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Uncertainty modeling process for semantic technology

PeerJ Computer Science ◽

10.7717/peerj-cs.77 ◽

2016 ◽

Vol 2 ◽

pp. e77 ◽

Cited By ~ 7

Author(s):

Rommel N. Carvalho ◽

Kathryn B. Laskey ◽

Paulo C.G. Da Costa

Keyword(s):

Knowledge Engineering ◽

Uncertainty Modeling ◽

Domain Model ◽

Proof Of Concept ◽

Semantic Technology ◽

Modeling Process ◽

Ontology Language ◽

Domain Semantics ◽

Probabilistic Ontology

The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

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Multi-Perspective Modeling of Healthcare Systems

International Journal of Privacy and Health Information Management ◽

10.4018/ijphim.2017070101 ◽

2017 ◽

Vol 5 (2) ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Ignace Djitog ◽

Hamzat Olanrewaju Aliyu ◽

Mamadou Kaba Traoré

Keyword(s):

Specific Problem ◽

Discrete Event ◽

Healthcare Systems ◽

Proof Of Concept ◽

System Specification ◽

Disease Propagation ◽

Dynamic Update ◽

Event System ◽

Simulation Based

This paper presents a multi-perspective approach to Modeling and Simulation (M&S) of Healthcare Systems (HS) such that different perspectives are defined and integrated together. The interactions between the isolated perspectives are done through dynamic update of models output-to-parameter integration during concurrent simulations. Most often, simulation-based studies of HS in the literature focus on specific problem like allocation of resources, disease propagation, and population dynamics that are studied with constant parameters from their respective experimental frames throughout the simulation. The proposed idea provides a closer representation of the real situation and helps to capture the interactions between seemingly independent concerns - and the effects of such interactions - in simulation results. The article provides a DEVS (Discrete Event System Specification)-based formalization of the loose integration of the different perspectives, an Object-Oriented framework for its realization and a case study as illustration and proof of concept.

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