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Related Experiment Video

Updated: Aug 11, 2025

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Published on: April 11, 2019

ProFAB-open protein functional annotation benchmark.

A Samet Özdilek¹, Ahmet Atakan^2,3, Gökhan Özsarı^2,4

¹Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.

Briefings in Bioinformatics

|February 3, 2023

Summary

This summary is machine-generated.

ProFAB is an open platform for benchmarking protein function prediction methods. It provides curated datasets and tools to ensure fair comparison of machine learning algorithms for accurate protein annotation.

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Last Updated: Aug 11, 2025

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

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A Protocol for Computer-Based Protein Structure and Function Prediction

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An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

Bioinformatics
Computational Biology
Machine Learning

Background:

Increasing protein sequence data necessitates accurate computational functional annotation.
Existing machine learning methods face challenges in dataset construction and performance evaluation.
Need for reliable benchmarks to compare protein function prediction tools.

Purpose of the Study:

To introduce ProFAB (Open Protein Functional Annotation Benchmark), a platform for fair comparison of protein function prediction methods.
To address issues related to reliable dataset creation and standardized evaluation protocols.
To facilitate the development and validation of machine learning algorithms for protein annotation.

Main Methods:

Development of ProFAB, an open infrastructure for benchmarking.
Provision of filtered and preprocessed protein annotation datasets.
Implementation of options for training and evaluating prediction methods.

Main Results:

ProFAB offers a standardized framework for comparing protein function prediction tools.
The platform ensures fair evaluation by providing consistent datasets and settings.
Facilitates the use of ready-to-use datasets and machine learning algorithms.

Conclusions:

ProFAB enables reliable assessment of protein function prediction methods.
It supports annotation based on Gene Ontology (GO) terms and Enzyme Commission (EC) numbers.
The platform benefits computational and experimental researchers in the field.