Results 61 to 70 of about 183,998 (331)

User Validation in Ontology Alignment

open access: yes, 2016
User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of automated alignment algorithms. In this paper we present a broad study on user validation of ontology alignments that encompasses three distinct but interrelated aspects: the profile of the user, the services of the alignment system ...
Dragisic, Zlatan   +5 more
openaire   +3 more sources

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

open access: yesMolecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker   +16 more
wiley   +1 more source

Ontological quality control in large-scale, applied ontology matching [PDF]

open access: yes, 2013
To date, large-scale applied ontology mapping has relied greatly on label matching and other relatively simple syntactic features. In search of more holistic and accurate alignment, we offer a suite of partially overlapping ontology mapping heuristics ...
Legg, Catherine, Sarjant, Samuel
core   +2 more sources

Data Linking with Ontology Alignment [PDF]

open access: yes, 2012
It is a trend to publish RDF data on the web, so that users can share information semantically. Then, linking isolated data sets together is highly needed. I would like to reduce the comparison scale by isolating the types of resources to be compared, so that it enhances the accuracy of the linking process.
openaire   +2 more sources

Ontology Alignment with FOAM++

open access: yesInternational Journal of Computer Applications, 2011
The rapid use of ontology in distributed systems as a knowledge representation mechanism, has led to a demand for ontology alignment process due to the heterogeneity arising between two or more ontology describing the same domain. Although many alignments tools have been proposed to reinforce the interoperability between different ontologies, most of ...
Akram Selah, AbdulHameed Haddad
openaire   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

open access: yesMolecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero   +11 more
wiley   +1 more source

On partitioning for ontology alignment [PDF]

open access: yes, 2017
On Partitioning for Ontology Alignment?Sunny Pereira1, Valerie Cross1, Ernesto Jiménez-Ruiz21Miami University, Oxford, OH 45056, United States2University of Oslo, Norway1 IntroductionOntology Alignment (OA) is the process of determining the mappings ...
Cross, V., Jimenez-Ruiz, E., Pereira, S.
core  

Shiva: A Framework for Graph Based Ontology Matching [PDF]

open access: yes, 2014
Since long, corporations are looking for knowledge sources which can provide structured description of data and can focus on meaning and shared understanding.
Darbari, Hemant   +3 more
core   +1 more source

Reduced vascular leakage correlates with breast carcinoma T regulatory cell infiltration but not with metastatic propensity

open access: yesMolecular Oncology, EarlyView.
A mouse model for vascular normalization and a human breast cancer cohort were studied to understand the relationship between vascular leakage and tumor immune suppression. For this, endothelial and immune cell RNAseq, staining for vascular function, and immune cell profiling were employed.
Liqun He   +8 more
wiley   +1 more source

An Industry-Ready Machine Learning Ontology

open access: yesApplied Sciences
This article presents an industry-ready ontology for the machine learning domain, which is named “ML Ontology”. While based on lightweight modelling languages, ML ontology provides novel features including built-in queries and quality assurance, as well ...
Bernhard G. Humm
doaj   +1 more source

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