ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2020
Predicting Tumor Cell Response to Synergistic Drug Combinations Using a Novel Simplified Deep Learning Model.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 15 citations in OpenAlex.
- PAIRWISE: Deep Learning-based Prediction of Effective Personalized Drug Combinations in Cancer.Research square · 2026Article
- Artificial intelligence for breast cancer management.Communications medicine · 2026Review
- Uncovering the mechanisms of synergistic drug combinations in non-small cell lung cancer through metagene-based classification.PloS one · 2026Article
- Accurate prediction of synergistic drug combination using a multi-source information fusion framework.BMC biology · 2025Article
- Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways.Scientific reports · 2025Article
- Anticancer drug synergy prediction based on CatBoost.PeerJ. Computer science · 2025Article
- Using DeepSignalingFlow to mine signaling flows interpreting mechanism of synergy of cocktails.NPJ systems biology and applications · 2024Article
- TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.Genomics, proteomics & bioinformatics · 2024Article
- DKPE-GraphSYN: a drug synergy prediction model based on joint dual kernel density estimation and positional encoding for graph representation.Frontiers in genetics · 2024Article
- Combination therapy synergism prediction for virus treatment using machine learning models.PloS one · 2024Article
- SYNDEEP: a deep learning approach for the prediction of cancer drugs synergy.Scientific reports · 2023Article
- A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer.PLoS computational biology · 2023Article
- SYNPRED: prediction of drug combination effects in cancer using different synergy metrics and ensemble learning.GigaScience · 2022Article
- PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.Briefings in bioinformatics · 2022Article
- Deep learning-based multi-drug synergy prediction model for individually tailored anti-cancer therapies.Frontiers in pharmacology · 2022Article
- Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects.Briefings in bioinformatics · 2021Review
- Predicting Anticancer Drug Response With Deep Learning Constrained by Signaling Pathways.Frontiers in bioinformatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug combinations targeting multiple targets/pathways are believed to be able to reduce drug resistance. Computational models are essential for novel drug combination discovery. In this study, we proposed a new simplified deep learning model,
Indexed as
Identifiers
33936513PMC8075535W3159462434What 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.