ArticleBioinformatics (Oxford, England)2017
Cancer Hallmarks Analytics Tool (CHAT): a text mining approach to organize and evaluate scientific literature on cancer.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
61 citing papers in PubMed.
- Article
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- IARC Workshop on the Key Characteristics of Carcinogens: Assessment of End Points for Evaluating Mechanistic Evidence of Carcinogenic Hazards.Environmental health perspectives · 2025Article
- Developing foundations for biomedical knowledgebases from literature using large language models - A systematic assessment.Computational and structural biotechnology journal · 2025Article
- BioKGrapher: Initial evaluation of automated knowledge graph construction from biomedical literature.Computational and structural biotechnology journal · 2024Article
- Unlocking hidden potential: advancements, approaches, and obstacles in repurposing drugs for cancer therapy.British journal of cancer · 2024Review
- Text mining for contexts and relationships in cancer genomics literature.Bioinformatics (Oxford, England) · 2024Article
- A Second Career for p53 as A Broad-Spectrum Antiviral?Viruses · 2023Article
- Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models.International journal of molecular sciences · 2023Article
- Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer.International journal of molecular sciences · 2023Article
- Molecular Genetic Characteristics ofGenes · 2023Article
- A survey on clinical natural language processing in the United Kingdom from 2007 to 2022.NPJ digital medicine · 2022Review
- Migration/Differentiation-Associated LncRNAGenes · 2022Article
- Single-cell dissection of remodeled inflammatory ecosystem in primary and metastatic gallbladder carcinoma.Cell discovery · 2022Article
- PARP targeted Auger emitter therapy with [EJNMMI research · 2022Article
- Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.Journal for immunotherapy of cancer · 2022Article
- Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma.Scientific reports · 2022Article
- Whole-Genome Sequencing of 100 Genomes Identifies a Distinctive Genetic Susceptibility Profile of Qatari Patients with Hypertension.Journal of personalized medicine · 2022Article
- Use of MS-GUIDE for identification of protein biomarkers for risk stratification of patients with prostate cancer.Clinical proteomics · 2022Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
motivationTo understand the molecular mechanisms involved in cancer development, significant efforts are being invested in cancer research. This has resulted in millions of scientific articles. An efficient and thorough review of the existing literature is crucially important to drive new research. This time-demanding task can be supported by emerging computational approaches based on text mining which offer a great opportunity to organize and retrieve the desired information efficiently from sizable databases. One way to organize existing knowledge on cancer is to utilize the widely accepted framework of the Hallmarks of Cancer. These hallmarks refer to the alterations in cell behaviour that characterize the cancer cell.
resultsWe created an extensive Hallmarks of Cancer taxonomy and developed automatic text mining methodology and a tool (CHAT) capable of retrieving and organizing millions of cancer-related references from PubMed into the taxonomy. The efficiency and accuracy of the tool was evaluated intrinsically as well as extrinsically by case studies. The correlations identified by the tool show that it offers a great potential to organize and correctly classify cancer-related literature. Furthermore, the tool can be useful, for example, in identifying hallmarks associated with extrinsic factors, biomarkers and therapeutics targets. AVAILABILITY AND IMPLEMENTATION: CHAT can be accessed at: http://chat.lionproject.net. The corpus of hallmark-annotated PubMed abstracts and the software are available at: http://chat.lionproject.net/about. CONTACT: simon.baker@cl.cam.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.