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Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts
2006
BMC Bioinformatics
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We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. ...
Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. ...
The full contents of the supplement are available online at http://www.biomedcentral.com/1471-2105/7?issue=S3. ...
doi:10.1186/1471-2105-7-s3-s4
pmid:17134477
pmcid:PMC1764448
fatcat:jg4tzqgmvrht3d7kbtgtspjcge
Biomedical text mining and its applications in cancer research
2013
Journal of Biomedical Informatics
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The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. ...
Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. ...
[91] developed classifiers for the automatic identification of schemes from abstracts to help cancer risk assessment. ...
doi:10.1016/j.jbi.2012.10.007
pmid:23159498
fatcat:xd7j77sbwfhklkat6tael64lbq
CERC: an interactive content extraction, recognition, and construction tool for clinical and biomedical text
2020
BMC Medical Informatics and Decision Making
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and extracting salient information from clinical and biomedical text. ...
In this work, we develop an interactive content extraction, recognition, and construction system (CERC) that combines machine learning and visualization techniques with domain knowledge for highlighting ...
, Chris Kwan, Eunho Kwon, Di Liu, Joe Malecki, Autumn Phillips, and Peijue Zhang, who helped with the initial usage and testing of the anonymized data generated from the customizable information extraction ...
doi:10.1186/s12911-020-01330-8
pmid:33323109
fatcat:neac7vl5fncibnx3kxcktyqmba
Target discovery from data mining approaches
2009
Drug Discovery Today
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Acknowledgements We wish to thank Dr Pavel Pospisil and Dr Lakshmanan K. Iyer for their helpful discussions in this project. ...
First, an initial list of 15 genes (seed genes) that are well known to be related to prostate cancer was collected from a curated database, Online Mendelian Inheritance in Man (OMIM; also see Box 1). ...
For the text mining approach, all abstracts related to the keywords 'HCV' and 'protein interactions' were retrieved and subjected to gene name recognition and human expert curation. ...
doi:10.1016/j.drudis.2008.12.005
pmid:19135549
fatcat:plsts2psuvclneuhgd5tlianwi
Target discovery from data mining approaches
2012
Drug Discovery Today
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Acknowledgements We wish to thank Dr Pavel Pospisil and Dr Lakshmanan K. Iyer for their helpful discussions in this project. ...
First, an initial list of 15 genes (seed genes) that are well known to be related to prostate cancer was collected from a curated database, Online Mendelian Inheritance in Man (OMIM; also see Box 1). ...
For the text mining approach, all abstracts related to the keywords 'HCV' and 'protein interactions' were retrieved and subjected to gene name recognition and human expert curation. ...
doi:10.1016/j.drudis.2011.12.006
pmid:22178890
fatcat:c7k3puzntbhcrmzjlw6uvgxhny
Automated recognition of malignancy mentions in biomedical literature
2006
BMC Bioinformatics
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Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. ...
Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related ...
of Medicine for access to MEDLINE; and Richard Wooster for corpus provision. ...
doi:10.1186/1471-2105-7-492
pmid:17090325
pmcid:PMC1657036
fatcat:no7r2il3ybh5ncwop5xhpez6ma
The Treasury Chest of Text Mining: Piling Available Resources for Powerful Biomedical Text Mining
2021
BioChem
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The array of documents that can be used ranges from scientific literature to patents or clinical data, and the biomedical concepts often include, despite not being limited to genes, proteins, drugs, and ...
When applied to biomedical literature, text mining is named biomedical text mining and its specificity lies in both the type of analyzed documents and the language and concepts retrieved. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/biochem1020007
fatcat:qve6xgoxuvbwzpqz6q45s7wlly
Extracting Concepts for Precision Oncology from the Biomedical Literature
2021
AMIA Annual Symposium Proceedings
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This paper describes an initial dataset and automatic natural language processing (NLP) method for extracting concepts related to precision oncology from biomedical research articles. ...
The best-performing model achieved a precision of 63.8%, a recall of 71.9%, and an F1 of 67.1. ...
[14] developed a corpus and extracted relations between prostate cancer and genes from abstracts using a maximum entropy classifier. ...
pmid:34457142
pmcid:PMC8378653
fatcat:3zm7sb3rujaxjcotp3wwgmiv7y
Extracting Concepts for Precision Oncology from the Biomedical Literature
[article]
2020
arXiv
pre-print
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This paper describes an initial dataset and automatic natural language processing (NLP) method for extracting concepts related to precision oncology from biomedical research articles. ...
The best-performing model achieved a precision of 63.8%, a recall of 71.9%, and an F1 of 67.1. ...
[14] developed a corpus and extracted relations between prostate cancer and genes from abstracts using a maximum entropy classifier. ...
arXiv:2010.00074v1
fatcat:rgq6yymifrd7jdb4r7knzm2w74
Text mining of cancer-related information: Review of current status and future directions
2014
International Journal of Medical Informatics
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The F-measure of NER ranges between 80% and 90%, while that of IE for simple tasks is in the high 90s. ...
Methods: A review of the research on TM of cancer-related information was carried out. ...
The NCI Thesaurus provides definitions and synonyms of nearly 10,000 cancers and related diseases, 8000 single agents and combination therapies and a range of other cancer-related topics. ...
doi:10.1016/j.ijmedinf.2014.06.009
pmid:25008281
fatcat:c3ifkrjacjgghdm6kz65flh434
Combining literature text mining with microarray data: advances for system biology modeling
2011
Briefings in Bioinformatics
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At the same time, the publication of databases of biological information and of experimental datasets generated by high-throughput methods is in great expansion, and a wealth of annotated gene databases ...
Under this scenario, this article reviews the knowledge discovery systems that fuse information from the literature, gathered by text mining, with microarray data for enriching the lists of down and upregulated ...
An example of association derived with Anni 2.0. is: 'Gene KLK3 is bound to the prostate cancer, more specifically with malignant neoplasm of prostate'. ...
doi:10.1093/bib/bbr018
pmid:21677032
fatcat:lvtg7ea74ngb5h6i2ywss6cjru
Molecular profiling of thyroid cancer subtypes using large-scale text mining
2014
BMC Medical Genomics
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Conclusions: Identification of key genes and pathways plays a central role in understanding the molecular biology of thyroid cancer. ...
Identifying the most relevant genes and biological pathways reported in the thyroid cancer literature is vital for understanding of the disease and developing targeted therapeutics. ...
For instance, a maximum entropy-based named entity recognizer and relation recognizer were applied to find relations between prostate cancer and genes [23] . ...
doi:10.1186/1755-8794-7-s3-s3
pmid:25521965
pmcid:PMC4290788
fatcat:ga2yy4owpfcmjbsuuly4tei2r4
Context-specific interaction networks from vector representation of words
2019
Nature Machine Intelligence
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2018 pre-print arXiv:1801.03011v2 fatcat:mtod672vafa47kbv7rosoqcqbaOther Versions
Here we present INtERAcT, a novel approach to extract protein-protein interactions from a corpus of biomedical articles related to a broad range of scientific domains in a completely unsupervised way. ...
INtERAcT exploits vector representation of words, computed on a corpus of domain specific knowledge, and implements a new metric that estimates an interaction score between two molecules in the space where ...
The project leading to this application has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 668858. ...
doi:10.1038/s42256-019-0036-1
fatcat:3p6cvpw3hfhtviuumdok36myde
The Clinical Role of SRSF1 Expression in Cancer: A Review of the Current Literature
2022
Applied Sciences
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Methods: Our review is based on English articles published in the MEDLINE/PubMed medical library between 2000 and 2021. ...
We retrieved articles that were specifically related to SRSF1 and cancers, and we excluded other reviews and meta-analyses. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12052268
fatcat:6wfcupr3xrhsti3alhrau6csne
Natural Language Processing methods and systems for biomedical ontology learning
2011
Journal of Biomedical Informatics
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from free-text documents. ...
One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. ...
We thank the two anonymous reviewers of this whose insightful critiques and suggestions have helped us improve the quality and completeness of this review. ...
doi:10.1016/j.jbi.2010.07.006
pmid:20647054
pmcid:PMC2990796
fatcat:hnyc5k4iobdzpatclwihaiw4wu
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