ReviewBriefings in bioinformatics2021
Recent advances of automated methods for searching and extracting genomic variant information from biomedical literature.
Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- VarChat: the generative AI assistant for the interpretation of human genomic variations.Bioinformatics (Oxford, England) · 2024Article
- Automatic extraction of ranked SNP-phenotype associations from text using a BERT-LSTM-based method.BMC bioinformatics · 2023Article
- The global prevalence and ethnic heterogeneity of iron-refractory iron deficiency anaemia.Orphanet journal of rare diseases · 2023Article
- ViMRT: a text-mining tool and search engine for automated virus mutation recognition.Bioinformatics (Oxford, England) · 2023Article
- tmVar 3.0: an improved variant concept recognition and normalization tool.Bioinformatics (Oxford, England) · 2022Article
- Variomes: a high recall search engine to support the curation of genomic variants.Bioinformatics (Oxford, England) · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationTo obtain key information for personalized medicine and cancer research, clinicians and researchers in the biomedical field are in great need of searching genomic variant information from the biomedical literature now than ever before. Due to the various written forms of genomic variants, however, it is difficult to locate the right information from the literature when using a general literature search system. To address the difficulty of locating genomic variant information from the literature, researchers have suggested various solutions based on automated literature-mining techniques. There is, however, no study for summarizing and comparing existing tools for genomic variant literature mining in terms of how to search easily for information in the literature on genomic variants.
resultsIn this article, we systematically compared currently available genomic variant recognition and normalization tools as well as the literature search engines that adopted these literature-mining techniques. First, we explain the problems that are caused by the use of non-standard formats of genomic variants in the PubMed literature by considering examples from the literature and show the prevalence of the problem. Second, we review literature-mining tools that address the problem by recognizing and normalizing the various forms of genomic variants in the literature and systematically compare them. Third, we present and compare existing literature search engines that are designed for a genomic variant search by using the literature-mining techniques. We expect this work to be helpful for researchers who seek information about genomic variants from the literature, developers who integrate genomic variant information from the literature and beyond.
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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.