ArticleThe Plant cell2013
The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.
Article in The Plant cell, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Decoding Nano-Bio Interactions: Gene Regulatory Networks in Advanced Drug Loading.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Extracting knowledge networks from plant scientific literature: potato tuber flesh color as an exemplary trait.BMC plant biology · 2021Article
- WTO, an ontology for wheat traits and phenotypes in scientific publications.Genomics & informatics · 2020Article
- The research on gene-disease association based on text-mining of PubMed.BMC bioinformatics · 2018Article
- CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.International journal of molecular sciences · 2017Article
- DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species.Scientific reports · 2017Article
- Omics Data Complementarity Underlines Functional Cross-Communication in Yeast.Journal of integrative bioinformatics · 2017Article
- Cross-species Conservation of context-specific networks.BMC systems biology · 2016Article
- Leaf responses to mild drought stress in natural variants of Arabidopsis.Plant physiology · 2015Article
- CARFMAP: A Curated Pathway Map of Cardiac Fibroblasts.PloS one · 2015Article
- Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis.BMC bioinformatics · 2015Article
- What Is Stress? Dose-Response Effects in Commonly Used in Vitro Stress Assays.Plant physiology · 2014Article
- Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis.The Plant cell · 2014Article
- Manually curated database of rice proteins.Nucleic acids research · 2014Article
- Root systems biology: integrative modeling across scales, from gene regulatory networks to the rhizosphere.Plant physiology · 2013Review
- Computational drug repositioning through heterogeneous network clustering.BMC systems biology · 2013Article
- RLIMS-P 2.0: A Generalizable Rule-Based Information Extraction System for Literature Mining of Protein Phosphorylation Information.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.
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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.