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MedGraph: An experimental semantic information retrieval method using knowledge graph embedding for the biomedical citations indexed in PubMed [article]

Islam Akef Ebeid, Elizabeth Pierce
2021 arXiv   pre-print
First, we introduce MedGraph, a knowledge graph embedding-based method that provides semantic relevance retrieval and ranking for the biomedical literature indexed in PubMed.  ...  In addition, our results provide evidence that semantic approaches to search and relevance in biomedical digital libraries that rely on knowledge graph modeling offer better search relevance results when  ...  Knowledge graphs were then born as a data model used to store information and data semantically.  ... 
arXiv:2112.06348v2 fatcat:iplogenjqfbsphnkfplzmz4qxe

Ontologies and Knowledge Graphs in Oncology Research

Marta Contreiras Silva, Patrícia Eugénio, Daniel Faria, Catia Pesquita
2022 Cancers  
A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies  ...  The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right.  ...  The immense potential of ontologies and the knowledge graph paradigm to support cancer research data management and analysis is increasingly recognized by the oncology research community as an essential  ... 
doi:10.3390/cancers14081906 pmid:35454813 pmcid:PMC9029532 fatcat:t6erzohmvnextkix4infnk7kza

Accelerating COVID-19 research with graph mining and transformer-based learning [article]

Ilya Tyagin and Ankit Kulshrestha and Justin Sybrandt and Krish Matta and Michael Shtutman and Ilya Safro
2021 arXiv   pre-print
The Allen Institute for AI and collaborators announced the availability of a rapidly growing open dataset of publications, the COVID-19 Open Research Dataset (CORD-19).  ...  We present an automated general purpose hypothesis generation systems AGATHA-C and AGATHA-GP for COVID-19 research. The systems are based on graph-mining and the transformer model.  ...  We use the PyTorch BigGraph heterogeneous graph embedding library to learn = 512 dimensional vector embeddings for each node of our large semantic graph.  ... 
arXiv:2102.07631v2 fatcat:7jjv6jcsm5cx5gx6lo4be347yy

Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge [article]

Mohamad Yaser Jaradeh, Allard Oelen, Kheir Eddine Farfar, Manuel Prinz, Jennifer D'Souza, Gábor Kismihók, Markus Stocker, Sören Auer
2019 arXiv   pre-print
In this paper, we present the first steps towards a knowledge graph based infrastructure that acquires scholarly knowledge in machine actionable form thus enabling new possibilities for scholarly knowledge  ...  Results suggest that users were intrigued by the novelty of the proposed infrastructure and by the possibilities for innovative scholarly knowledge processing it could enable.  ...  ACKNOWLEDGMENTS This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536) and the TIB Leibniz Information Centre for Science and Technology.  ... 
arXiv:1901.10816v3 fatcat:muqej6fmwfe3bdbl3xmsiqxtqa

Implementing interoperable provenance in biomedical research

V. Curcin, S. Miles, R. Danger, Y. Chen, R. Bache, A. Taweel
2014 Future generations computer systems  
Providing evidence for validating research is of particular importance in the biomedical domain, where the strength of the results depends on the data sources and processes used.  ...  The provenance of a piece of data refers to knowledge about its origin, in terms of entities and actors involved in its creation, e.g. data sources used, operations carried out on them, and users enacting  ...  The provenance data shown was created during their user tests. We would also like to thank the reviewers of an earlier version of this paper for helpful comments and constructive suggestions.  ... 
doi:10.1016/j.future.2013.12.001 fatcat:tnl3l5s7tnhdlfcfejgvec5gfe

Entrez Neuron RDFa: a pragmatic semantic web application for data integration in neuroscience research

Matthias Samwald, Ernest Lim, Peter Masiar, Luis Marenco, Huajun Chen, Thomas Morse, Pradeep Mutalik, Gordon Shepherd, Perry Miller, Kei-Hoi Cheung
2009 Studies in Health Technology and Informatics  
The amount of biomedical data available in Semantic Web formats has been rapidly growing in recent years.  ...  Where possible, the application makes use of entities from the Open Biomedical Ontologies (OBO) and the 'HCLS knowledgebase' developed by the W3C Interest Group for Health Care and Life Science.  ...  The work was also funded in part by the Konrad Lorenz Institute for Evolution and Cognition Research.  ... 
pmid:19745321 pmcid:PMC3753668 fatcat:l5m7xkexb5farewthnwcacmw6m

BioHackathon 2015: Semantics of data for life sciences and reproducible research

Rutger A. Vos, Toshiaki Katayama, Hiroyuki Mishima, Shin Kawano, Shuichi Kawashima, Jin-Dong Kim, Yuki Moriya, Toshiaki Tokimatsu, Atsuko Yamaguchi, Yasunori Yamamoto, Hongyan Wu, Peter Amstutz (+65 others)
2020 F1000Research  
We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences  ...  We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.  ...  ) and the Database Center for Life Science (DBCLS).  ... 
doi:10.12688/f1000research.18236.1 pmid:32308977 pmcid:PMC7141167 fatcat:oaglnztjrrhpvgluujl3reudoe

Utopia documents: linking scholarly literature with research data

T. K. Attwood, D. B. Kell, P. McDermott, J. Marsh, S. R. Pettifer, D. Thorne
2010 Bioinformatics  
ACKNOWLEDGEMENTS We thank all Portland Press staff for helping to realize the Semantic BJ, and, in particular, Rhonda Oliver and Audrey McCulloch for their courage, patience and positive collaboration.  ...  For their help and guidance in developing interfaces and plugins to their software, we also thank: Gert Vriend and Bas Vroling ( Conflict of Interest: none declared.  ...  Utopia Documents brings us a step closer to integrated scholarly literature and research data.  ... 
doi:10.1093/bioinformatics/btq383 pmid:20823323 pmcid:PMC2935404 fatcat:6g5dto5pqfetbordnwmukpyymi

Towards an Open Research Knowledge Graph

Sören Auer, Sanjeet Mann
2018 The Serials librarian  
Challenges include incentivizing researchers to participate and creating the training data needed to automate the generation of knowledge graphs in all fields of research.  ...  In his NASIG vision session, Auer introduced attendees to knowledge graphs and explained how they could make scientific research more discoverable, efficient, and collaborative.  ...  Look at Open Street Maps. It's not just a map, but hundreds of maps for accessibility, bicycles, catastrophe prevention.  ... 
doi:10.1080/0361526x.2019.1540272 fatcat:cgrah5u4bffkrg42vzpcq6iuri

Representing Semantified Biological Assays in the Open Research Knowledge Graph [article]

Marco Anteghini, Jennifer D'Souza, Vitor A.P. Martins dos Santos, Sören Auer
2020 arXiv   pre-print
Herein, we present our work on the representation of semantified bioassays in the Open Research Knowledge Graph (ORKG).  ...  the ORKG for recording their bioassays and facilitate the organisation of research, according to FAIR principles.  ...  Supported by TIB Leibniz Information Centre for Science and Technology, the EU H2020 ERC project ScienceGRaph (GA ID: 819536) and the ITN PERICO (GA ID: 812968).  ... 
arXiv:2009.07642v1 fatcat:2qot3qcbungcln5lmo4ie4yhra

Knowledge-based Biomedical Data Science 2019 [article]

Tiffany J. Callahan, Ignacio J. Tripodi Computational Bioscience Program, Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus
2019 arXiv   pre-print
Here we survey the progress in the last year in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as on approaches for creating  ...  Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine.  ...  Evaluation of Knowledge Graph Embedding Approaches for Drug-Drug Interaction Prediction using Linked Open Data 50. Crichton G, Guo Y, Pyysalo S, Korhonen A. 2018.  ... 
arXiv:1910.06710v1 fatcat:kvz5k643zvhpdiq67blc2v33wi

Advancing translational research with the Semantic Web

Alan Ruttenberg, Tim Clark, William Bug, Matthias Samwald, Olivier Bodenreider, Helen Chen, Donald Doherty, Kerstin Forsberg, Yong Gao, Vipul Kashyap, June Kinoshita, Joanne Luciano (+11 others)
2007 BMC Bioinformatics  
A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains.  ...  It is based on common formats that support aggregation and integration of data drawn from diverse sources.  ...  We would like to thank Alzheimer Research Forum and Brainstage Research, Inc for contributing to part of the publication costs.  ... 
doi:10.1186/1471-2105-8-s3-s2 pmid:17493285 pmcid:PMC1892099 fatcat:sbsqc4hplba77fvazmrkeam2iy

An empirical meta-analysis of the life sciences linked open data on the web

Maulik R. Kamdar, Mark A. Musen
2021 Scientific Data  
not useful for data integration from a biomedical perspective.  ...  We envision that the LSLOD schema graph and the findings from this research will aid researchers who wish to query and integrate data and knowledge from multiple biomedical sources simultaneously on the  ...  Semantic heterogeneity across linked open data graphs.  ... 
doi:10.1038/s41597-021-00797-y pmid:33479214 fatcat:iealrgcwwbhjlicg7m43mj4mee

S2ORC: The Semantic Scholar Open Research Corpus [article]

Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, Dan S. Weld
2020 arXiv   pre-print
We hope this resource will facilitate research and development of tools and tasks for text mining over academic text.  ...  The corpus consists of rich metadata, paper abstracts, resolved bibliographic references, as well as structured full text for 8.1M open access papers.  ...  Finally, we thank the Semantic Scholar team for assisting with data access and system infrastructure.  ... 
arXiv:1911.02782v3 fatcat:oxdmyodlhvcplkcoyjnxtvu2ga

Semantic text mining for lignocellulose research

Marie-Jean Meurs, Caitlin Murphy, Ingo Morgenstern, Nona Naderi, Greg Butler, Justin Powlowski, Adrian Tsang, René Witte
2011 Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics - DTMBIO '11  
literature for relevant information, and at the same time providing rich and semantically linked information.  ...  Semantic technologies, including natural language processing (NLP), ontologies, semantic web services and web-based collaboration tools, promise to support users in dealing with complex data, thereby facilitating  ...  References to the original sources are integrated into the curated data, which allows us to automatically create links using standard Linked Data techniques: e.g., links from an organism mention in a research  ... 
doi:10.1145/2064696.2064705 fatcat:bno6bicjn5a6vljdzdkmsk2t4a
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