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Related Experiment Video

Updated: May 13, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

In-depth performance evaluation of PFP and ESG sequence-based function prediction methods in CAFA 2011 experiment.

Meghana Chitale1, Ishita K Khan, Daisuke Kihara

  • 1Department of Computer Science, Purdue University, 305 N, University Street, West Lafayette, Indiana 47907, USA.

BMC Bioinformatics
|March 22, 2013
PubMed
Summary

This study analyzes two Automatic Function Prediction (AFP) methods, PFP and ESG, using CAFA data. The findings offer insights into sequence similarity and function inference, aiding AFP method development.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing generates vast gene data, necessitating Automatic Function Prediction (AFP) methods.
  • Community-wide experiments like Critical Assessment of Function Annotation (CAFA) are crucial for evaluating AFP performance.
  • This study focuses on analyzing PFP and ESG, two sequence-based AFP methods, within the CAFA framework.

Purpose of the Study:

  • To perform a detailed analysis of the PFP and ESG methods using predictions submitted to CAFA.
  • To evaluate the performance of PFP and ESG in comparison to other established methods.
  • To explore variations in scoring functions and the impact of Gene Ontology term enrichment on prediction accuracy.

Main Methods:

  • Sequence-based function prediction using PFP and ESG algorithms.

Related Experiment Videos

Last Updated: May 13, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

  • Evaluation using four different performance measures against BLAST, Prior, and GOtcha.
  • Analysis of prediction accuracy across different functional categories.
  • Investigation of modified scoring functions and prior-enriched predictions.

    • Main Results:

    • PFP and ESG performance was evaluated against established methods like BLAST.
    • Prediction accuracies were assessed separately for various functional categories.
    • The study discusses successful and unsuccessful predictions made by PFP and ESG in comparison to BLAST.
    • The impact of alternative scoring and Gene Ontology term enrichment on PFP/ESG predictions was investigated.

    Conclusions:

    • The detailed analysis complements the official CAFA assessment.
    • Findings are valuable for users of PFP and ESG methods.
    • The study illuminates the relationship between sequence similarity and inferable functions from sequence data.