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PCfun: a hybrid computational framework for systematic characterization of protein complex function.

Varun S Sharma1,2, Andrea Fossati3,4, Rodolfo Ciuffa1

  • 1Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Switzerland.

Briefings in Bioinformatics
|June 20, 2022
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Summary
This summary is machine-generated.

Protein Complex Function predictor (PCfun) is a new computational framework that uses natural language processing to systematically annotate protein complex functions. This tool aids in understanding biological processes by predicting functions of macromolecular machines.

Keywords:
gene ontologymachine learningnatural language processingprotein complex function

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Area of Science:

  • Molecular Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Protein complexes are crucial for biological functions, mediating cellular states and phenotypes.
  • Identifying protein complex function is challenging despite advances in identifying their composition.

Purpose of the Study:

  • To introduce PCfun, the first computational framework for systematic protein complex function annotation using Gene Ontology (GO) terms.
  • To provide a novel tool for large-scale characterization of protein complex function.

Main Methods:

  • Developed PCfun using word embeddings from 1 million PubMed Central articles and natural language processing.
  • Employed an unsupervised nearest neighbor (NN) approach and a supervised Random Forest (RF) model.
  • Integrated both approaches using a hypergeometric statistical test for GO term enrichment.

Main Results:

  • PCfun accurately predicts protein complex functions by leveraging NLP and machine learning.
  • The framework systematically annotates protein complex functions using GO terms.
  • The study provides a computational framework to address the challenge of determining protein complex functions.

Conclusions:

  • PCfun offers a novel paradigm for the large-scale characterization of protein complex function.
  • The tool is expected to accelerate research in molecular biology and systems biology.
  • PCfun is available as an open-source package for broader scientific use.