ArticleCancer research2016
Systems Approaches to Cancer Biology.
Article in Cancer research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- BDDN: bayesian dynamic differential network analysis in cancer proteomics.BMC bioinformatics · 2026Article
- A Roadmap for the Future of Systems Biology in Cancer Research.Cancer research · 2025Review
- Systems Biology and Cytokines Potential Role in Lung Cancer Immunotherapy Targeting Autophagic Axis.Biomedicines · 2023Review
- Cancer systems epidemiology: Overcoming misconceptions and integrating systems approaches into cancer research.PLoS medicine · 2022Article
- Targeting HIF1-alpha/miR-326/ITGA5 axis potentiates chemotherapy response in triple-negative breast cancer.Breast cancer research and treatment · 2022Article
- Circadian and Immunity Cycle Talk in Cancer Destination: From Biological Aspects to In Silico Analysis.Cancers · 2022Review
- Redrawing therapeutic boundaries: microbiota and cancer.Trends in cancer · 2022Review
- Identification ofCell journal · 2021Article
- A Systems Approach to Brain Tumor Treatment.Cancers · 2021Review
- Clinical trial design: Past, present, and future in the context of big data and precision medicine.Cancer · 2020Review
- Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types.Frontiers in genetics · 2020Article
- Classification of Widely and Rarely Expressed Genes with Recurrent Neural Network.Computational and structural biotechnology journal · 2019Article
- Imaging and the completion of the omics paradigm in breast cancer.Der Radiologe · 2018Review
- A network modeling approach to elucidate drug resistance mechanisms and predict combinatorial drug treatments in breast cancer.Cancer convergence · 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
9 authors.
Funding
Abstract
Cancer systems biology aims to understand cancer as an integrated system of genes, proteins, networks, and interactions rather than an entity of isolated molecular and cellular components. The inaugural Systems Approaches to Cancer Biology Conference, cosponsored by the Association of Early Career Cancer Systems Biologists and the National Cancer Institute of the NIH, focused on the interdisciplinary field of cancer systems biology and the challenging cancer questions that are best addressed through the combination of experimental and computational analyses. Attendees found that elucidating the many molecular features of cancer inevitably reveals new forms of complexity and concluded that ensuring the reproducibility and impact of cancer systems biology studies will require widespread method and data sharing and, ultimately, the translation of important findings to the clinic. Cancer Res; 76(23); 6774-7. ©2016 AACR.
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.