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Discovering Informative Syntactic Relationships between Named Entities in Biomedical Literature

Annalisa Appice, Michelangelo Ceci, Corrado Loglisci
2010 2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications  
The discovery of new and potentially meaningful relationships between named entities in biomedical literature can take great advantage from the application of multirelational data mining approaches in  ...  Multi-relational approach to frequent pattern discovery allows to identify the verb-based relationships between the named entities which frequently occur in the corpora.  ...  of "informing" on the syntactic role (subject or object) of each entity and the kind of relationship (verb) eventually connecting them.  ... 
doi:10.1109/dbkda.2010.14 dblp:conf/dbkda/AppiceCL10 fatcat:kyowhpzeynelfcym76klqp3r2a

MBlab: Molecular Biodiversity Laboratory [chapter]

Corrado Loglisci, Annalisa Appice, Michelangelo Ceci, Donato Malerba, Floriana Esposito
2011 Communications in Computer and Information Science  
Technologies in available biomedical repositories do not yet provide adequate mechanisms to support the understanding and analysis of the stored content.  ...  These integrate sophisticated technologies and innovative approaches of Information Extraction, Data Mining and Machine Learning to perform descriptive tasks of knowledge discovery from biomedical repositories  ...  This work is in partial fulfillment of the research objectives of the project MBlab DM19410 "Molecular Biodiversity Laboratory".  ... 
doi:10.1007/978-3-642-27302-5_18 fatcat:semakj3pm5d3xbn43rc672crti

Application of Biomedical Text Mining [chapter]

Lejun Gong
2018 Artificial Intelligence - Emerging Trends and Applications  
This chapter emphasizes the two aspects in biomedical text mining involving static biomedical information recognization and dynamic biomedical information extraction using instance analysis from our previous  ...  Aiming at this massive literature to process, it could extract more biological information for mining biomedical knowledge.  ...  In this study, we focus on the dynamic process of biomedical entities, and extract dynamic biomedical information, namely association between biomedical entities, based on entity co-occurrence analysis  ... 
doi:10.5772/intechopen.75924 fatcat:5o27ptssi5fwzbelnpktkwplby

Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery

Svitlana Volkova, Doina Caragea, William H. Hsu, John Drouhard, Landon Fowles
2010 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology  
Biomedical entity extraction from unstructured web documents is an important task that needs to be performed in order to discover knowledge in the veterinary medicine domain.  ...  Specifically, these relationships are extracted by using a set of syntactic patterns and part-of-speech tagging.  ...  Some examples of such approaches include: dictionary-based bio-entity name recognition in biomedical literature [13] , protein name recognition using gazetteer [14] , and gene-disease relation extraction  ... 
doi:10.1109/wi-iat.2010.152 dblp:conf/webi/VolkovaCHDF10 fatcat:4fagc24q6rc65di6kfjphkuzr4

Discovering biomedical relations utilizing the World-wide Web

Sougata Mukherjea, Saurav Sahay
2006 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
To crate a Semantic Web for Life Sciences discovering relations between biomedical entities is essential.  ...  In this paper we present techniques to automatically discover biomedical relations from the World-wide Web.  ...  After that a Relation Annotator discovers the relations between the biomedical entities. It uses templates for patterns which specify relationships in sentences.  ... 
pmid:17094237 fatcat:nholn2wa65fyzcfefvhe2kcfqe

DISCOVERING BIOMEDICAL RELATIONS UTILIZING THE WORLD-WIDE WEB

SOUGATA MUKHERJEA, SAURAV SAHAY
2005 Biocomputing 2006  
To crate a Semantic Web for Life Sciences discovering relations between biomedical entities is essential.  ...  In this paper we present techniques to automatically discover biomedical relations from the World-wide Web.  ...  After that a Relation Annotator discovers the relations between the biomedical entities. It uses templates for patterns which specify relationships in sentences.  ... 
doi:10.1142/9789812701626_0016 fatcat:xmqteozp7rfu7lxqqomp2w4wzy

AUTHOR

Jong C. Park, Gary Geunbae Lee, Limsoon Wong
2006 ACM Transactions on Asian Language Information Processing  
In addition to conceptual relationships among biomedical terms, information about interactions among biomedical entities, as identified from the associated syntactic and discourse-related information among  ...  While the problem of biomedical NER is being resolved, the conceptual relationships among biomedical-named entities (or terms), often captured in ontologies, are also of much interest.  ...  The results of biomedical studies, as reported in the literature, sometimes include ones that are negatively qualified, in addition to those that are stated in a positive manner.  ... 
doi:10.1145/1131348.1131349 fatcat:2i4pqujvxnhhjouvdktphxdb3m

EDGAR: Extraction of Drugs, Genes And Relations from the Biomedical Literature

Thomas C. Rindflesch, Lorraine Tanabe, John N. Weinstein, Lawrence Hunter
1999 Biocomputing 2000  
about the terms found in biomedical abstracts.  ...  EDGAR (Extraction of Drugs, Genes and Relations) is a natural language processing system that extracts information about drugs and genes relevant to cancer from the biomedical literature.  ...  L.T. and J.N.W. are supported in part by funding from the Breast Cancer Task Force of the National Cancer Institute Division of Clinical Sciences.  ... 
doi:10.1142/9789814447331_0049 fatcat:dyebl3wchrfvfb3zukr2lypj3u

Proceedings of the Second International Symposium for Semantic Mining in Biomedicine

Sophia Ananiadou, Juliane Fluck
2006 BMC Bioinformatics  
Acknowledgements This article has been published as part of BMC Bioinformatics Volume 7, Supplement 3, 2006: Second International Symposium on Semantic Mining in Biomedicine.  ...  To discover knowledge hidden in the large amount of biomedical texts, we need text mining techniques which go to levels of linguistic processing deeper than simple lexical and syntactic processing.  ...  The analysis of highthroughput data in combination with textual extracted information about relationships of the investigated entities will allow biologists to make predictions about novel interactions  ... 
doi:10.1186/1471-2105-7-s3-s1 fatcat:h26jwoukezbvtgt73qlrfhyapy

Drug Disease Relation Extraction from Biomedical Literature Using NLP and Machine Learning

Wahiba Ben Abdessalem Karaa, Eman H. Alkhammash, Aida Bchir
2021 Mobile Information Systems  
These relations can be extracted from biomedical literature available on various databases. This study examines the extraction of semantic relations that can occur between diseases and drugs.  ...  The Support Vector Machine classifier uses these features to extract valuable semantic relationships among text entities.  ...  their field. ese relations can be discovered from a variety of texts in biomedical literature.  ... 
doi:10.1155/2021/9958410 doaj:8ef39a03dd8a47968219ca1fd1f38c65 fatcat:vt3fcxqsb5ahnkytwvrwivougq

Mining semantically related terms from biomedical literature

Goran Nenadić, Sophia Ananiadou
2006 ACM Transactions on Asian Language Information Processing  
Discovering links and relationships is one of the main challenges in biomedical research, as scientists are interested in uncovering entities that have similar functions, take part in the same processes  ...  This article discusses the extraction of such semantically related entities (represented by domain terms) from biomedical literature.  ...  ACKNOWLEDGMENTS The UK National Centre for Text Mining (NaCTeM, http://www.nactem.ac.uk) is funded by the Joint Information Systems Committee (JISC), the Biotechnoloy and Biological Sciences Research Council  ... 
doi:10.1145/1131348.1131351 fatcat:5yrw7ukbvnen7ahzzvvbr5omrm

BioKB - Text Mining and Semantic Technologies for Biomedical Content Discovery

Maria Biryukov, Valentin Groues, Venkata Satagopam, Reinhard Schneider
2018 Figshare  
The ever-increasing number of publicly available biomedical articles calls for automatic information extraction from digitized publi- cations.  ...  Extracted knowledge is stored in a knowledge base publicly available for both, human and machine access, via web interface and SPARQL end- point.  ...  between various entities involved in the biomedical processes [23] [24] [25] .  ... 
doi:10.6084/m9.figshare.6994121.v1 fatcat:7qncychbrjcj7ptwi7cpnpozxm

Text mining and its potential applications in systems biology

Sophia Ananiadou, Douglas B. Kell, Jun-ichi Tsujii
2006 Trends in Biotechnology  
With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload  ...  Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this.  ...  Semantic annotations reveal terms and named entities in the text, for example, genes and proteins. Deep parsing: provides relationships not explicitly stated among words in a sentence.  ... 
doi:10.1016/j.tibtech.2006.10.002 pmid:17045684 fatcat:ppkcfka7yrenjkz3z3ad4dj6ha

Text-mining approaches in molecular biology and biomedicine

M KRALLINGER, R ERHARDT, A VALENCIA
2005 Drug Discovery Today  
These technologies have a key role in integrating biomedical information through analysis of scientific literature.  ...  In this article, important applications such as the identification of biologically relevant entities in free text and the construction of literature-based networks of protein-protein interactions will  ...  They include tools that discover new relationships between relevant entities such as chemical substances and diseases, NLP systems that extract and structure information contained in clinical records,  ... 
doi:10.1016/s1359-6446(05)03376-3 pmid:15808823 fatcat:w5i3ciuq4zhk7oq4kbbv5wqfma

Extracting Biomarker Information Applying Natural Language Processing and Machine Learning

Md. Tawhidul Islam, Mostafa Shaikh, Abhaya Nayak, Shoba Ranganathan
2010 Bioinformatics and Biomedical Engineering (iCBBE), International Conference on  
In this paper, we detail an approach to a very specific task of information extraction namely, extracting biomarker information in biomedical literature.  ...  Finally, we identify the biomarker relationship among the biomedical entities (i.e., semantic relationship classification).  ...  Most of the development on this so far has focused on discovering gene-gene relations, proteinprotein relations or protein-protein interactions [2, 3, 6] from biomedical documents.  ... 
doi:10.1109/icbbe.2010.5514717 fatcat:jeuiavsuibfq3exbcbisimkebe
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