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BIOS: An Algorithmically Generated Biomedical Knowledge Graph
[article]
2022
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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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
2017
International Journal of Advanced Computer Science and Applications
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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
2014
International Journal of Bio-Science and Bio-Technology
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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
2015
BMC Medical Informatics and Decision Making
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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
2019
Sadhana (Bangalore)
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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
2011
PLoS ONE
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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
2012
BMC Bioinformatics
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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
2009
2009 IEEE International Conference on Bioinformatics and Biomedicine
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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
2010
International Journal of Functional Informatics and Personalised Medicine
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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
2017
Biotechnology & Biotechnological Equipment
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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]
2009
Studies in Computational Intelligence
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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
2010
BMC Bioinformatics
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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
2009
BMC Bioinformatics
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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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