ArticleScientific reports2015
Drug target optimization in chronic myeloid leukemia using innovative computational platform.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Multimodal gene and targeted drug therapy for chronic myelogenous leukemia using BIM/MCL-1 chimeric nanoparticle: computational target analysis and therapeutic validation.Nano convergence · 2026Article
- Data driven network inference and longitudinal transcriptomics unveil dynamic regulation in Chronic Lymphocytic Leukaemia models.NPJ systems biology and applications · 2026Article
- Potential signaling pathways, biomarkers, natural drugs, and chronic myeloid leukemia therapeutics.Frontiers in pharmacology · 2025Review
- Beyond IC50-A computational dynamic model of drug resistance in enzyme inhibition treatment.PLoS computational biology · 2024Article
- Localized immune surveillance of primary melanoma in the skin deciphered through executable modeling.Science advances · 2023Article
- Executable network of SARS-CoV-2-host interaction predicts drug combination treatments.NPJ digital medicine · 2022Article
- Executable cancer models: successes and challenges.Nature reviews. Cancer · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 3 countries.
Funding
Abstract
Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing drug resistance, caused by mutations and/or activation of alternative cellular pathways. To optimize drug development, one needs to systematically test all possible combinations of drug targets within the genetic network that regulates the disease. The BioModelAnalyzer (BMA) is a user-friendly computational tool that allows us to do exactly that. We used BMA to build a CML network-model composed of 54 nodes linked by 104 interactions that encapsulates experimental data collected from 160 publications. While previous studies were limited by their focus on a single pathway or cellular process, our executable model allowed us to probe dynamic interactions between multiple pathways and cellular outcomes, suggest new combinatorial therapeutic targets, and highlight previously unexplored sensitivities to Interleukin-3.
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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.