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Text Mining Biomedical Literature for Discovering Gene-to-Gene Relationships: A Comparative Study of Algorithms

Ying Liu, S.B. Navathe, J. Civera, V. Dasigi, A. Ram, B.J. Ciliax, R. Dingledine
2005 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
A number of computer algorithms have been developed for this task. Although these algorithms have demonstrated their usefulness for gene clustering, some basic problems remain.  ...  This paper describes our work on extracting functional keywords from MEDLINE for a set of genes that are isolated for further study from microarray experiments based on their differential expression patterns  ...  The authors would like to thank Brian Revennaugh and Alex Pivoshenk for research support.  ... 
doi:10.1109/tcbb.2005.14 pmid:17044165 fatcat:fn547ts72feezcihirysvxtsxu


2009 Biocomputing 2010  
We conclude that we can use relationships mined automatically from the literature as a knowledgebase for pharmacogenomics relationships.  ...  In this work, we assess the utility of text mining in extracting a network of drug-gene relationships automatically.  ...  The authors would like to thank R. Whaley for PharmGKB data. We thank our anonymous reviewers for their constructive comments.  ... 
doi:10.1142/9789814295291_0033 fatcat:osstnpl5w5bera7ymzo3htb4ra

Text Mining Genotype-Phenotype Relationships from Biomedical Literature for Database Curation and Precision Medicine

Ayush Singhal, Michael Simmons, Zhiyong Lu, Andrey Rzhetsky
2016 PLoS Computational Biology  
In this work, we present a highly accurate machine-learning-based text mining approach for mining complete genotypephenotype relationships from biomedical literature.  ...  However, the exponentially increasing size of biomedical literature and the limited ability of manual curators to discover the genotype-phenotype relationships "hidden" in text has led to delays in keeping  ...  Acknowledgments We extend our special thanks to Dr. Ioannis Xenarios and Alan Bridge from SwissProt for helpful discussion and suggestions about the current project. We are grateful to Dr.  ... 
doi:10.1371/journal.pcbi.1005017 pmid:27902695 pmcid:PMC5130168 fatcat:mr2xqlb6kbgjxg6wyy7e7skxfu

Improving the prediction of pharmacogenes using text-derived drug-gene relationships

Yael Garten, Nicholas P Tatonetti, Russ B Altman
2010 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
We conclude that we can use relationships mined automatically from the literature as a knowledgebase for pharmacogenomics relationships.  ...  In this work, we assess the utility of text mining in extracting a network of drug-gene relationships automatically.  ...  The authors would like to thank R. Whaley for PharmGKB data. We thank our anonymous reviewers for their constructive comments.  ... 
pmid:19908383 pmcid:PMC3092476 fatcat:5gw4ajqosja63a5btpase663yq

Learning the Structure of Biomedical Relationships from Unstructured Text

Bethany Percha, Russ B. Altman, K. Bretonnel Cohen
2015 PLoS Computational Biology  
The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining.  ...  Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice  ...  Identifying pharmacogenomic and drug-target relationships in biomedical text We evaluated EBC's ability to mine the literature for drug-gene pairs exemplifying two specific types of drug-gene relationships  ... 
doi:10.1371/journal.pcbi.1004216 pmid:26219079 pmcid:PMC4517797 fatcat:lvc57v6l4jfehb2ppl7qyaim2u

Identifying genotype-phenotype relationships in biomedical text

Maryam Khordad, Robert E. Mercer
2017 Journal of Biomedical Semantics  
One important type of information contained in biomedical research literature is the newly discovered relationships between phenotypes and genotypes.  ...  Because of the large quantity of literature, a reliable automatic system to identify this information for future curation is essential.  ...  Acknowledgements Support for this work was provided through a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant to Robert E. Mercer.  ... 
doi:10.1186/s13326-017-0163-8 pmid:29212530 pmcid:PMC5719522 fatcat:r5smrbuvtved5lw3zleirahcpa

A semantic relationship mining method among disorders, genes, and drugs from different biomedical datasets

Li Zhang, Jiamei Hu, Qianzhi Xu, Fang Li, Guozheng Rao, Cui Tao
2020 BMC Medical Informatics and Decision Making  
However, most of the existing studies focused on a single dataset.  ...  Methods First, a variety of biomedical datasets were converted into RDF triple data; then, multisource biomedical datasets were integrated into a storage system using a data integration algorithm.  ...  Acknowledgments We thank the anonymous reviewers for their careful reading of our manuscript and their insightful comments. We also thank Dr. Irmgard Willcockson for language editing.  ... 
doi:10.1186/s12911-020-01274-z pmid:33317518 fatcat:tdvwqesdpva4nobfygbv5lql4a


2011 Biocomputing 2012  
Much of the PGx knowledge has been embedded in biomedical literature and there is a growing interest to develop text mining approaches to extract such knowledge.  ...  In this paper, we present a study to rank candidate gene-drug relations using Latent Dirichlet Allocation (LDA) model.  ...  The authors would like to thank Dr. Josh Denny at Vanderbilt University for providing KnowledgeMap, Dr. Hongfang Liu at Mayo Clinic for providing Biothesaurus, Dr.  ... 
doi:10.1142/9789814366496_0041 fatcat:v7gih4dywne57lg3fzekwdfvf4

A knowledge-driven conditional approach to extract pharmacogenomics specific drug–gene relationships from free text

Rong Xu, QuanQiu Wang
2012 Journal of Biomedical Informatics  
Therefore there is a need to develop automatic approaches to extract structured PGx-specific drug-gene relationships from unstructured free text literature.  ...  Scientific literature is one of the most comprehensive knowledge sources for PGx-specific drug-gene relationships.  ...  Acknowledgments Both Rong Xu and QuanQiu Wang have conceived the idea, designed and implemented the algorithms. Xu has written the paper.  ... 
doi:10.1016/j.jbi.2012.04.011 pmid:22561026 pmcid:PMC4589154 fatcat:jf7gb3srsjhfjnml7kjy5nhgbu

Finding Complex Biological Relationships in Recent PubMed Articles Using Bio-LDA

Huijun Wang, Ying Ding, Jie Tang, Xiao Dong, Bing He, Judy Qiu, David J. Wild, Jörg Langowski
2011 PLoS ONE  
provides a useful resource for the discovery of recent information concerning genes, diseases, compounds and the interactions between them.  ...  In this paper, we describe an algorithm called Bio-LDA that uses extracted biological terminology to automatically identify latent topics, and provides a variety of measures to uncover putative relations  ...  Acknowledgments We would like to thank Michel Dumontier and Glen Newton at Carleton University for their suggestions on this work. Author Contributions  ... 
doi:10.1371/journal.pone.0017243 pmid:21448266 pmcid:PMC3063155 fatcat:mxtdsdbvszeotmqdmmll2azfuu

Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization)

Elina Tjioe, Michael W Berry, Ramin Homayouni
2010 BMC Bioinformatics  
Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics.  ...  Conclusions: FAUN not only assists researchers to use biomedical literature efficiently, but also provides utilities for knowledge discovery.  ...  Acknowledgements This work is supported by NIH-subcontract (HD052472) involving the University of Tennessee, University of Memphis, Oak Ridge National Laboratory, and the University of British Columbia  ... 
doi:10.1186/1471-2105-11-s6-s14 pmid:20946597 pmcid:PMC3026361 fatcat:bfkhgpyt2bdkzac6mccrmxcke4

dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text

Rong Xu, Li Li, QuanQiu Wang
2014 BMC Bioinformatics  
of free-text published biomedical literature.  ...  "D1 due to D2") as a seed to automatically discover other patterns specifying similar semantic relationships among diseases.  ...  Acknowledgements We would like to thank Yang Chen for drawing the two risk graphs.  ... 
doi:10.1186/1471-2105-15-105 pmid:24725842 pmcid:PMC3998061 fatcat:mxm4y7efvrdqjeasb2fe6kthpi


2006 Biocomputing 2007  
We present a computational method that combines data extracted from the literature with data from curated sources in order to uncover possible gene-disease relationships that are not directly stated or  ...  Motivation: The promises of the post-genome era disease-related discoveries and advances have yet to be fully realized, with many opportunities for discovery hiding in the millions of biomedical papers  ...  Figure 1 . 1 Overview and data flow of the computational method presented here to mine the biomedical literature for genes potentially related to a specific disease.  ... 
doi:10.1142/9789812772435_0004 fatcat:jqgo3x5q4bdb5lhj4ezer2oun4

Biomolecular Relationships Discovered from Biological Labyrinth and Lost in Ocean of Literature: Community Efforts Can Rescue Until Automated Artificial Intelligence Takes Over

Rajinder Gupta, Shrikant S. Mantri
2016 Frontiers in Genetics  
ISSUES IN LITERATURE TEXT MINING Let's have a deeper look into major concerns in biological literature mining: (A) Non-standard naming conventions: The absence of any standard naming convention(s) for  ...  Automating the literature mining process using NER, IE and IR has proved to be a costly affair with slow progress as compared to the speed of new research getting published.  ...  Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest  ... 
doi:10.3389/fgene.2016.00046 pmid:27066067 pmcid:PMC4814459 fatcat:w4ulvpfszfemnjt3iqiixwvzla

Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature

Ayush Singhal, Michael Simmons, Zhiyong Lu
2016 JAMIA Journal of the American Medical Informatics Association  
The aim of this work is to design a tool that automates the extraction of disease-related mutations from biomedical text to advance database curation for the support of precision medicine.  ...  Materials and Methods We developed a machine-learning (ML) based method to automatically identify the mutations mentioned in the biomedical literature related to a particular disease.  ...  ACKNOWLEDGEMENTS We are grateful to Dr Chih-Hsuan Wei for helping with data access through PubTator and other support. We are also thankful to Emily Doughty and Dr  ... 
doi:10.1093/jamia/ocw041 pmid:27121612 pmcid:PMC4926749 fatcat:hwgdv3xkzrf5vkpe2huwn372m4
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