ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2012
Ranking gene-drug relationships in biomedical literature using Latent Dirichlet Allocation.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Prevalence of exposure to pharmacogenetic drugs by the Saudis treated at the health care centers of the Ministry of National Guard.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2022Article
- A longitudinal study of topic classification on Twitter.PeerJ. Computer science · 2022Article
- Evaluation of clustering and topic modeling methods over health-related tweets and emails.Artificial intelligence in medicine · 2021Article
- A semantic relationship mining method among disorders, genes, and drugs from different biomedical datasets.BMC medical informatics and decision making · 2020Article
- Methodologically grounded semantic analysis of large volume of chilean medical literature data applied to the analysis of medical research funding efficiency in Chile.Journal of biomedical semantics · 2020Article
- Revealing the microbial assemblage structure in the human gut microbiome using latent Dirichlet allocation.Microbiome · 2020Article
- Predicting biomedical relationships using the knowledge and graph embedding cascade model.PloS one · 2019Article
- Annotation and detection of drug effects in text for pharmacovigilance.Journal of cheminformatics · 2018Article
- Co-occurrence of medical conditions: Exposing patterns through probabilistic topic modeling of snomed codes.Journal of biomedical informatics · 2018Article
- The research on gene-disease association based on text-mining of PubMed.BMC bioinformatics · 2018Article
- Article
- Identifying Plant-Human Disease Associations in Biomedical Literature: A Case Study.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach.PloS one · 2016Article
- Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.PLoS computational biology · 2015Article
- Concept Modeling-based Drug Repositioning.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Secondary use of clinical data: the Vanderbilt approach.Journal of biomedical informatics · 2014Article
- A semi-supervised approach to extract pharmacogenomics-specific drug-gene pairs from biomedical literature for personalized medicine.Journal of biomedical informatics · 2013Article
- An iterative searching and ranking algorithm for prioritising pharmacogenomics genes.International journal of computational biology and drug design · 2013Article
- Use of Internet of Things for Chronic Disease Management: An Overview.Journal of medical signals and sensorsReview
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Drug responses vary greatly among individuals due to human genetic variations, which is known as pharmacogenomics (PGx). 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. Our approach consists of three steps: 1) recognize gene and drug entities in MEDLINE abstracts; 2) extract candidate gene-drug pairs based on different levels of co-occurrence, including abstract level, sentence level, and phrase level; and 3) rank candidate gene-drug pairs using multiple different methods including term frequency, Chi-square test, Mutual Information (MI), a reported Kullback-Leibler (KL) distance based on topics derived from LDA (LDA-KL), and a newly defined probabilistic KL distance based on LDA (LDA-PKL). We systematically evaluated these methods by using a gold standard data set of gene-drug relations derived from PharmGKB. Our results showed that the proposed LDA-PKL method achieved better Mean Average Precision (MAP) than any other methods, suggesting its promising uses for ranking and detecting PGx relations.
Indexed as
Identifiers
22174297PMC4095990What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.