ReviewOncology reports2015
Human cancer databases (review).
Review in Oncology reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed, 88 citations in OpenAlex.
- A comparative evaluation of canine meningioma supporting the canine patient as a naturally occurring animal model for human meningioma: a report from the NCI Comparative Brain Tumor Consortium (CBTC) meningioma pathology board.Veterinary oncology (London, England) · 2026Article
- The NLRP1 Emerges as a Promising Therapeutic Target and Prognostic Biomarker Across Multiple Cancer Types: A Comprehensive Pan-Cancer Analysis.Cancer medicine · 2025Article
- Metabolite-Induced Apoptosis byNutrients · 2025Article
- Article
- Artificial intelligence methods available for cancer research.Frontiers of medicine · 2024Review
- Investigation of the efficacy of siRNA-mediated KRAS gene silencing in pancreatic cancer therapy.PeerJ · 2024Article
- Review
- OncoCardioDB: a public and curated database of molecular information in onco-cardiology/cardio-oncology.Database : the journal of biological databases and curation · 2023Article
- Translating Data Science Results into Precision Oncology Decisions: A Mini Review.Journal of clinical medicine · 2023Review
- Survival Analysis of Oncological Patients Using Machine Learning Method.Healthcare (Basel, Switzerland) · 2022Article
- Synthesis and Anticancer Potential of New Hydroxamic Acid Derivatives as Chemotherapeutic Agents.Applied biochemistry and biotechnology · 2022Article
- Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions.Life (Basel, Switzerland) · 2022Review
- Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis.Genomics, proteomics & bioinformatics · 2022Review
- The Cancer Research Database (CRDB): Integrated Platform to Gain Statistical Insight Into the Correlation Between Cancer and COVID-19.JMIR cancer · 2022Article
- Life Entrapped in a Network of Atavistic Attractors: How to Find a Rescue.International journal of molecular sciences · 2022Review
- Progressing Towards a Human-Centric Approach in Cancer Research.Frontiers in oncology · 2022Review
- Recent updates on anticancer mechanisms of polyphenols.Frontiers in cell and developmental biology · 2022Review
- MutaXome: A Novel Database for Identified Somatic Variations ofCancer informatics · 2022Article
- Review
- Exploring polyps to colon carcinoma voyage: can blocking the crossroad halt the sequence?Journal of cancer research and clinical oncology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is one of the four major non‑communicable diseases (NCD), responsible for ~14.6% of all human deaths. Currently, there are >100 different known types of cancer and >500 genes involved in cancer. Ongoing research efforts have been focused on cancer etiology and therapy. As a result, there is an exponential growth of cancer‑associated data from diverse resources, such as scientific publications, genome‑wide association studies, gene expression experiments, gene‑gene or protein‑protein interaction data, enzymatic assays, epigenomics, immunomics and cytogenetics, stored in relevant repositories. These data are complex and heterogeneous, ranging from unprocessed, unstructured data in the form of raw sequences and polymorphisms to well‑annotated, structured data. Consequently, the storage, mining, retrieval and analysis of these data in an efficient and meaningful manner pose a major challenge to biomedical investigators. In the current review, we present the central, publicly accessible databases that contain data pertinent to cancer, the resources available for delivering and analyzing information from these databases, as well as databases dedicated to specific types of cancer. Examples for this wealth of cancer‑related information and bioinformatic tools have also been provided.
Indexed as
Identifiers
What 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.