Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners

The directory includes a comprehensive set of scripts for running Genetic Algorithm simulations and performing parameter calculations, including I', I*, I₀, σ₀², and TP rate. All analyses are demonstrated using both orthologous and paralogous protein families.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-09
DOI
https://doi.org/10.5281/zenodo.14624294
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners

Zenodo (CERN European Organization for Nuclear Research)
Bioinformatics and Genomic Networks
article

Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners

article en

Abstract

The directory includes a comprehensive set of scripts for running Genetic Algorithm simulations and performing parameter calculations, including I', I*, I₀, σ₀², and TP rate. All analyses are demonstrated using both orthologous and paralogous protein families.

Zenodo (CERN European Organization for Nuclear Research)
Universidade de Brasília (BR)
Openalex Percentile: Top 62%
Bioinformatics and Genomic Networks
DOIOpen Access PDFOpenAlex
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Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS