ArticleNPJ breast cancer2016
"Big Data" for Breast Cancer: Where to look and what you will find.
Article in NPJ breast cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Recent Advances and Emerging Directions in Machine Learning-Based Breast Cancer Drug Discovery: A Comprehensive Review.Breast cancer (Dove Medical Press) · 2026Review
- Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis.Diagnostics (Basel, Switzerland) · 2022Review
- MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.Cancer research · 2022Article
- Article
- Evaluation of the role of KPNA2 mutations in breast cancer prognosis using bioinformatics datasets.BMC cancer · 2022Article
- FGF7/FGFR2-JunB signalling counteracts the effect of progesterone in luminal breast cancer.Molecular oncology · 2022Article
- Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets.Cancer biology & medicine · 2022Article
- Tumor-Infiltrating CD8 T Cells Predict Clinical Breast Cancer Outcomes in Young Women.Cancers · 2020Article
- Supporting data sharing.NPJ breast cancer · 2019Article
- In silico screening for ERα down modulators identifies thioridazine as an anti-proliferative agent in primary, 4OH-tamoxifen-resistant and Y537S ERα-expressing breast cancer cells.Cellular oncology (Dordrecht, Netherlands) · 2018Article
- Applications of RNA Indexes for Precision Oncology in Breast Cancer.Genomics, proteomics & bioinformatics · 2018Review
- Estrogen-activated MDM2 disrupts mammary tissue architecture through a p53-independent pathway.Oncotarget · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Accessing the massive amount of breast cancer data that is currently publically available may seem daunting to the brand new graduate student embarking on his/her first project or even to the seasoned lab leader, who may wish to explore a new avenue of investigation. In this review, we provide an overview of data resources focusing on high-throughput data and on cancer-related data resources. While not intended as an exhaustive list, the information included in this review will provide a jumping off point with descriptions of and links to the various data resources of interest. The review is divided into six sections: (1) Compendia of data resources; (2) Biomolecular Repository "Hubs"' (3) A list of cancer-related data resources, which provides information on contents of the resource and whether the resource enables upload and analysis of investigator provided data; (4) A list of seminal publications containing specific breast cancer data, e.g., publications from METBRIC, Sanger, TCGA; (5) A list of journals focused on data science that include cancer-related "Big Data"; and (6) Miscellaneous resources.
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.