Network-based methods for identifying critical pathways of complex diseases: a survey.

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics and Proteomics

Background:

• Complex diseases, including cancers, arise from multifactorial genetic and pathway dysregulation.
• Understanding disease mechanisms necessitates integrating diverse high-throughput data, such as genomics and proteomics.
• Network-based approaches are emerging as key tools for pathway analysis.

Purpose of the Study:

• To provide a comprehensive overview of current network-based pathway analysis methods.
• To critically evaluate the algorithmic benefits and limitations of seven major methods.
• To offer insights for developing next-generation pathway analysis tools.

Main Methods:

• Systematic review of seven prominent network-based pathway analysis algorithms.
• Algorithmic perspective analysis of method strengths and weaknesses.
• Discussion of challenges in contemporary pathway analysis.

Main Results:

• Identified key benefits and limitations across seven distinct network-based pathway analysis methods.
• Provided an algorithmic comparison to inform method selection and development.
• Highlighted critical challenges for future advancements in the field.

Conclusions:

• Network-based pathway analysis is essential for dissecting complex disease mechanisms.
• Algorithmic evaluation is crucial for advancing pathway analysis methodologies.
• Addressing identified challenges will pave the way for more robust next-generation methods.