A cross-study analysis of drug response prediction in cancer cell lines
To enable personalized cancer treatment, machine learning models have been developed
to predict drug response as a function of tumor and drug features. However, most algorithm …
to predict drug response as a function of tumor and drug features. However, most algorithm …
Advancing targeted protein degradation via multiomics profiling and artificial intelligence
M Duran-Frigola, M Cigler… - Journal of the American …, 2023 - ACS Publications
Only around 20% of the human proteome is considered to be druggable with small-molecule
antagonists. This leaves some of the most compelling therapeutic targets outside the reach …
antagonists. This leaves some of the most compelling therapeutic targets outside the reach …
SynergyFinder plus: toward better interpretation and annotation of drug combination screening datasets
Combinatorial therapies have been recently proposed to improve the efficacy of anticancer
treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug …
treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug …
DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal
Combinatorial therapies that target multiple pathways have shown great promises for
treating complex diseases. DrugComb (https://drugcomb. org/) is a web-based portal for the …
treating complex diseases. DrugComb (https://drugcomb. org/) is a web-based portal for the …
Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery
Artificial intelligence transforms drug discovery, with phenotype-based approaches
emerging as a promising alternative to target-based methods, overcoming limitations like …
emerging as a promising alternative to target-based methods, overcoming limitations like …
Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque
Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a
major challenge, so that multiple views of a given biological event can be considered …
major challenge, so that multiple views of a given biological event can be considered …
Cancer mutations converge on a collection of protein assemblies to predict resistance to replication stress
Rapid proliferation is a hallmark of cancer associated with sensitivity to therapeutics that
cause DNA replication stress (RS). Many tumors exhibit drug resistance, however, via …
cause DNA replication stress (RS). Many tumors exhibit drug resistance, however, via …
A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
PS Mundi, FS Dela Cruz, A Grunn, D Diolaiti… - Cancer discovery, 2023 - AACR
Predicting in vivo response to antineoplastics remains an elusive challenge. We performed
a first-of-kind evaluation of two transcriptome-based precision cancer medicine …
a first-of-kind evaluation of two transcriptome-based precision cancer medicine …
A complete graph-based approach with multi-task learning for predicting synergistic drug combinations
Motivation Drug combination therapy shows significant advantages over monotherapy in
cancer treatment. Since the combinational space is difficult to be traversed experimentally …
cancer treatment. Since the combinational space is difficult to be traversed experimentally …
OncoLoop: A network-based precision cancer medicine framework
A Vasciaveo, JM Arriaga, FN De Almeida, M Zou… - Cancer discovery, 2023 - AACR
Prioritizing treatments for individual patients with cancer remains challenging, and
performing coclinical studies using patient-derived models in real time is often unfeasible …
performing coclinical studies using patient-derived models in real time is often unfeasible …