ReviewFrontiers in genetics2021
Omics and Computational Modeling Approaches for the Effective Treatment of Drug-Resistant Cancer Cells.
Review in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed.
- Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Deciphering molecular pathways driving cancer invasion and metastasis: advances and therapeutic prospects.Frontiers in oncology · 2025Review
- Unlocking the Molecular Secrets of Antifolate Drug Resistance: A Multi-Omics Investigation of the NCI-60 Cell Line Panel.Biomedicines · 2023Article
- Successes and challenges in modeling heterogeneous BRAFFrontiers in oncology · 2023Review
- Editorial: Computational and systematic analysis of multi-omics data for drug discovery and development.Frontiers in medicine · 2023Article
- Characterization of prevalent tyrosine kinase inhibitors and their challenges in glioblastoma treatment.Frontiers in chemistry · 2023Review
- Liquid Biopsy at Home: Delivering Precision Medicine for Patients with Cancer During the COVID-19 Pandemic.The oncologist · 2022Article
- From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer.International journal of molecular sciences · 2022Review
- Editorial: Molecular Targeted Therapy in Oncology: Lessons From Pharmacogenetics and Pharmacoepigenetics.Frontiers in molecular biosciences · 2022Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemotherapy is a mainstream cancer treatment, but has a constant challenge of drug resistance, which consequently leads to poor prognosis in cancer treatment. For better understanding and effective treatment of drug-resistant cancer cells, omics approaches have been widely conducted in various forms. A notable use of omics data beyond routine data mining is to use them for computational modeling that allows generating useful predictions, such as drug responses and prognostic biomarkers. In particular, an increasing volume of omics data has facilitated the development of machine learning models. In this mini review, we highlight recent studies on the use of multi-omics data for studying drug-resistant cancer cells. We put a particular focus on studies that use computational models to characterize drug-resistant cancer cells, and to predict biomarkers and/or drug responses. Computational models covered in this mini review include network-based models, machine learning models and genome-scale metabolic models. We also provide perspectives on future research opportunities for combating drug-resistant cancer cells.
Indexed as
Identifiers
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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 Socratic graph.