PHENSIM: Phenotype Simulator.

Area of Science:

• Computational biology
• Systems biology
• Cellular signaling

Background:

• Connecting cell biology knowledge to experimental data remains a challenge.
• Difficulties in experimental design arise from interpreting cell and tissue physiopathological status.
• Existing methods for validation are often labor-intensive, expensive, and hard to interpret.

Purpose of the Study:

• To introduce PHENSIM, a computational tool for simulating cell phenotype alterations.
• To leverage systems biology and signaling pathways for predicting experimental outcomes.
• To provide a tool for inferring cell line behavior and predicting drug administration effects.

Main Methods:

• Utilizing a systems biology approach to model cell phenotype changes.
• Exploiting signaling pathways to simulate biomolecule activation/inhibition.
• Developing a computational tool with pathway maps from three model organisms.

Main Results:

• PHENSIM accurately predicts outcomes for drug administration, knockdown, gene transduction, and exosomal cargo exposure.
• Benchmark testing using transcriptomics data from NCBI GEO demonstrated high prediction accuracy.
• Four case studies confirmed the reliability and capabilities of the PHENSIM methodology.

Conclusions:

• PHENSIM offers a reliable and accurate method for simulating cell phenotype responses.
• The tool facilitates predictions in various experimental contexts, reducing experimental burden.
• PHENSIM is available as a standalone Java application and a web-based interface for broader accessibility.