Pitfalls of machine learning models for protein-protein interaction networks.

ABSTRACT:

Motivation

Protein-protein interactions (PPIs) are essential to understanding biological pathways as well as their roles in development and disease. Computational tools, based on classic machine learning, have been successful at predicting PPIs in silico, but the lack of consistent and reliable frameworks for this task has led to network models that are difficult to compare and discrepancies between algorithms that remain unexplained.

Results

To better understand the underlying inference mechanisms that underpin these models, we designed an open-source framework for benchmarking that accounts for a range of biological and statistical pitfalls while facilitating reproducibility. We use it to shed light on the impact of network topology and how different algorithms deal with h

SUBMITTER: Lannelongue L 

PROVIDER: S-EPMC10868344 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature