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Molecular Targeted Therapy

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Target Prediction Model for Natural Products Using Transfer Learning.

International journal of molecular sciences
A large proportion of lead compounds are derived from natural products. However, most natural products have not been fully tested for their targets. To help resolve this problem, a model using transfer learning was built to predict targets for natura...

The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Biochimica et biophysica acta. Reviews on cancer
Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clinical trials. Recent advances in computational methods, notably causal artificial intelligence, and availability of rich clinico-genomic databases have ...

Methodological advances in the discovery of novel neuroblastoma therapeutics.

Expert opinion on drug discovery
INTRODUCTION: Neuroblastoma is a cancer of the sympathetic nervous system that causes up to 15% of cancer-related deaths among children. Among the ~1,000 newly diagnosed cases per year in Europe, more than half are classified as high-risk, with a 5-y...

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools.

Journal of gastrointestinal cancer
PURPOSE: Computational approaches have been used at different stages of drug development with the purpose of decreasing the time and cost of conventional experimental procedures. Lately, techniques mainly developed and applied in the field of artific...

A functional module states framework reveals transcriptional states for drug and target prediction.

Cell reports
Cells are complex systems in which many functions are performed by different genetically defined and encoded functional modules. To systematically understand how these modules respond to drug or genetic perturbations, we develop a functional module s...