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Multi-species Conserved Sequences

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Related Experiment Video

Updated: Jul 23, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD.

Andreas Grigorjew¹, Artur Gynter¹, Fernando H C Dias¹

¹Department of Computer Science, University of Helsinki, Helsinki, Finland.

|July 17, 2023

Summary

This study introduces pairwise alignment-safety to reveal robust amino acid positions across suboptimal sequence alignments. This method enhances understanding of protein biodiversity beyond optimal alignments alone.

Keywords:

Dynamic programming Needleman-Wunsch algorithm Protein folding Sequence alignment Suboptimal alignments

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Last Updated: Jul 23, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

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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
Genomics

Background:

Sequence alignments are fundamental in life science research.
Current methods primarily focus on optimal alignments, neglecting valuable information from suboptimal solutions.
Relying solely on optimal alignments is insufficient for large-scale biodiversity studies, such as those at the tree-of-life scale.

Purpose of the Study:

To introduce a novel concept, pairwise alignment-safety, to analyze suboptimal sequence alignment solutions.
To uncover amino acid positions that are consistently conserved across all suboptimal alignments.
To provide a more comprehensive understanding of sequence relationships and protein universe biodiversity.

Main Methods:

Development of the EMERALD software library for alignment-safety inference.
Application of EMERALD to a large dataset of 400,000 sequences from the SwissProt database.
Analysis of suboptimal alignment solutions to identify robustly shared amino acid positions.

Main Results:

Demonstration that pairwise alignment-safety can identify amino acid positions robustly shared across suboptimal alignments.
Successful implementation and application of the EMERALD software library.
Analysis of 400k SwissProt sequences provides insights into conserved regions beyond optimal alignment findings.

Conclusions:

Pairwise alignment-safety offers a powerful approach to extract more information from sequence alignment data.
The EMERALD library facilitates the inference of alignment-safety, enhancing biodiversity exploration.
This method addresses the limitations of relying solely on optimal alignments in large-scale biological sequence analysis.