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BIOS: An Algorithmically Generated Biomedical Knowledge Graph [article]

Sheng Yu, Zheng Yuan, Jun Xia, Shengxuan Luo, Huaiyuan Ying, Sihang Zeng, Jingyi Ren, Hongyi Yuan, Zhengyun Zhao, Yucong Lin, Keming Lu, Jing Wang (+2 others)
2022 arXiv   pre-print
For decades, these knowledge graphs have been developed via expert curation; however, this method can no longer keep up with today's AI development, and a transition to algorithmically generated BioMedKGs  ...  In this work, we introduce the Biomedical Informatics Ontology System (BIOS), the first large-scale publicly available BioMedKG generated completely by machine learning algorithms.  ...  Wikidata is a general domain knowledge graph.  ... 
arXiv:2203.09975v2 fatcat:fztgdsyywbbdvaymkcm24665g4

Bio-SODA: Enabling Natural Language Question Answering over Knowledge Graphs without Training Data [article]

Ana Claudia Sima, Tarcisio Mendes de Farias, Maria Anisimova, Christophe Dessimoz, Marc Robinson-Rechavi, Erich Zbinden, Kurt Stockinger
2021 arXiv   pre-print
Bio-SODA uses a generic graph-based approach for translating user questions to a ranked list of SPARQL candidate queries.  ...  Furthermore, Bio-SODA uses a novel ranking algorithm that includes node centrality as a measure of relevance for selecting the best SPARQL candidate query.  ...  The ranking algorithm combines syntactic and semantic similarity, as well as node centrality in the knowledge graph.  ... 
arXiv:2104.13744v4 fatcat:swbggfd34ng7fgh7qaiqokvxa4

Bio-signals compression using auto-encoder

Sunilkumar K. N., Shivashankar Shivashankar, Keshavamurthy Keshavamurthy
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
Wearable devices will rely on size, resources and battery capacity; we need a novel algorithm to robustly control memory and the energy of the device.  ...  The rapid growth of the technology has led to numerous auto encoders that guarantee the results by extracting feature selection from time and frequency domain in an efficient way.  ...  In the same manner, two weighted matrices and are generated to categories both the graphs.  ... 
doi:10.11591/ijece.v11i1.pp424-433 fatcat:c3z56qu3rbci3enqgnjzfc5dji

Artificial Intelligence in Bio-Medical Domain

Muhammad Salman, Abdul Wahab, Omair Ahmad, Basit Raza, Khalid Latif
2017 International Journal of Advanced Computer Science and Applications  
AI, ANN, ML) is revolutionizing the field of biomedical and healthcare.  ...  Finally, an investigation of some expert systems and applications is made.  ...  II METHODS USED IN AI FOR BIOMEDICAL DOMAIN Methods Reference Implemented Technique Decision-theoretic [29] Markov decision processes Search methods [30] Forward and Backward Graph-based [  ... 
doi:10.14569/ijacsa.2017.080842 fatcat:p7wurhzxwbd3vhcixkity2y5iq

Biomarker Discovery and Data Visualization Tool for Ovarian Cancer Screening

Ki-Seok Cheong, Hye-Jeong Song, Chan-Young Park, Jong-Dae Kim, Yu-Seop Kim
2014 International Journal of Bio-Science and Bio-Technology  
With the increase in various clinical applications of medical knowledge, a large amount of bio-data have been generated.  ...  In this paper, we report on an integrated software tool developed to enable the easy analysis of such bio-data for diagnostic medical testing without the deep use of statistics-related knowledge or tools  ...  to the generation of useful knowledge [4] .  ... 
doi:10.14257/ijbsbt.2014.6.2.17 fatcat:bl2nblcq45dixhvjgbyhqxp6ua

Developing a hybrid dictionary-based bio-entity recognition technique

Min Song, Hwanjo Yu, Wook-Shin Han
2015 BMC Medical Informatics and Decision Making  
Bio-entity extraction is a pivotal component for information extraction from biomedical literature.  ...  The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques.  ...  In the general English domain, Frantzi et al.  ... 
doi:10.1186/1472-6947-15-s1-s9 pmid:26043907 pmcid:PMC4460617 fatcat:23l3qeel65fc7ldqsyh2fkatca

Bio-molecular event extraction by integrating multiple event-extraction systems

Amit Majumder, Asif Ekbal, Sudip Kumar Naskar
2019 Sadhana (Bangalore)  
Event extraction from biomedical text is a very important task in text mining and natural language processing.  ...  We perform event detection and event classification in one step using an ensemble of classifiers. For event argument extraction, we also use an ensemble of classification models.  ...  Following features are generated from the dependency graph. Features for in-type edges: These features are generated using information of incoming edges for a node in the graph.  ... 
doi:10.1007/s12046-018-0998-4 fatcat:srwmr7w55varbkbhxyfpb7f2pm

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

Lindsey Bell, Rajesh Chowdhary, Jun S. Liu, Xufeng Niu, Jinfeng Zhang, Ying Xu
2011 PLoS ONE  
Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks.  ...  Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places.  ...  Acknowledgments We would like to thank all the authors and curators of the databases we have used in this work for their contributions to a well maintained scientific knowledge base, which made this study  ... 
doi:10.1371/journal.pone.0021474 pmid:21738677 pmcid:PMC3124513 fatcat:5qfmq6samfb2nedy4tjijcwupy

OLSVis: an animated, interactive visual browser for bio-ontologies

Steven Vercruysse, Aravind Venkatesan, Martin Kuiper
2012 BMC Bioinformatics  
This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph.  ...  More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS).  ...  Background Ontologies constitute an increasingly important knowledge resource.  ... 
doi:10.1186/1471-2105-13-116 pmid:22646023 pmcid:PMC3394205 fatcat:lvajwtzjhbbjhj6aqj2dcveipa

Biomedical Relationship Extraction from Literature Based on Bio-semantic Token Subsequences

Jayasimha R. Katukuri, Ying Xie, Vijay V. Raghavan
2009 2009 IEEE International Conference on Bioinformatics and Biomedicine  
In this paper, two supervised learning algorithms based on newly-defined "bio-semantic token subsequence" are proposed for multi-class biomedical relationship extraction.  ...  Relationship Extraction (RE) from biomedical literature is an important and challenging problem in both text mining and bioinformatics.  ...  [1] presented a kernel method called "all-paths graph kernel" for protein-protein interaction extraction. Their method uses the dependency graph in defining a graph kernel.  ... 
doi:10.1109/bibm.2009.74 dblp:conf/bibm/KatukuriXR09 fatcat:msz3ra7fbffmtfpj2jdqv7jfwy

Biomedical Relationship Extraction from literature based on bio-semantic token subsequences

Jayasimha R. Katukuri, Ying Xie, Vijay V. Raghavan
2010 International Journal of Functional Informatics and Personalised Medicine  
In this paper, two supervised learning algorithms based on newly-defined "bio-semantic token subsequence" are proposed for multi-class biomedical relationship extraction.  ...  Relationship Extraction (RE) from biomedical literature is an important and challenging problem in both text mining and bioinformatics.  ...  [1] presented a kernel method called "all-paths graph kernel" for protein-protein interaction extraction. Their method uses the dependency graph in defining a graph kernel.  ... 
doi:10.1504/ijfipm.2010.033243 fatcat:yj6pgwsbfzdafgrl2i6sn2coja

Intelligent mining of large-scale bio-data: Bioinformatics applications

Farahnaz Sadat Golestan Hashemi, Mohd Razi Ismail, Mohd Rafii Yusop, Mahboobe Sadat Golestan Hashemi, Mohammad Hossein Nadimi Shahraki, Hamid Rastegari, Gous Miah, Farzad Aslani
2017 Biotechnology & Biotechnological Equipment  
The present paper argues how artificial intelligence can assist bio-data analysis and gives an up-to-date review of different applications of bio-data mining.  ...  KEYWORDS Bioinformatics; data mining; artificial intelligence; intelligent knowledge discovery; bio-data analysis; heuristic algorithms Abbreviations AUC area under the curve BADH betaine aldehyde dehydrogenase  ...  A method for analysing the huge and complicated datasets is to generate integrated data-knowledge networks allowing biomedical researchers to analyse the results of an experiment in the context of existing  ... 
doi:10.1080/13102818.2017.1364977 fatcat:qmbiss53wfggtc7ayj2ysgt5rq

Bio-medical Ontologies Maintenance and Change Management [chapter]

Arash Shaban-Nejad, Volker Haarslev
2009 Studies in Computational Intelligence  
To manage a large volume of evolving bio-medical data of various types, one needs to employ several techniques from areas such as knowledge representation, semantic web and databases.  ...  We also survey various potential changes in biomedical ontologies, with actual examples from some of the most popular ontologies in the biomedical domain.  ...  Ontologies are extensively being employed in biomedical systems to share common terminologies, provide annotation, and organize and extract knowledge from a domain of interest.  ... 
doi:10.1007/978-3-642-02193-0_6 fatcat:4lwfhekchnfj3cnto2tqgxwv6m

Highlights of the BioTM 2010 workshop on advances in bio text mining

Thomas Abeel, Sofie Van Landeghem, Roser Morante, Vincent Van Asch, Yves Van de Peer, Walter Daelemans, Yvan Saeys
2010 BMC Bioinformatics  
This meeting report gives an overview of the keynote lectures, the panel discussion and a selection of the contributed presentations. The workshop was held in Gent, Belgium on May 10-11.  ...  To this end, the workshop started with an extensive tutorial on text mining in the bio-sciences, providing sufficient background knowledge for novices.  ...  Bio-Creative, BioNLP Shared Task, ...)  ... 
doi:10.1186/1471-2105-11-s5-i1 pmcid:PMC2956387 fatcat:uxijwmf4djerjcoh5hg72s6i4m

Bio-jETI: a framework for semantics-based service composition

Anna-Lena Lamprecht, Tiziana Margaria, Bernhard Steffen
2009 BMC Bioinformatics  
The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world ofbioinformatics services.  ...  These issues are taken care of at the semantic level by Bio-jETl's model checking and synthesis features.  ...  We used the synthesis algorithm to generate the sequence of these missing steps.  ... 
doi:10.1186/1471-2105-10-s10-s8 pmid:19796405 pmcid:PMC2755829 fatcat:cxje3kun4banhoocelv6p56uvq
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