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Updated: Feb 20, 2026

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

DREAM-Stellar: parallel and space efficient exact local alignment.

Evelin Aasna^1,2, Simon Gene Gottlieb³, Marcel Ehrhardt³

¹Max-Planck-Institut für Molekulare Genetik, Ihnestraße 63-73, 14195, Berlin, Berlin, Germany. aasna@molgen.mpg.de.

BMC Bioinformatics

|February 19, 2026

Summary

This summary is machine-generated.

DREAM-Stellar efficiently finds local alignments in large genomic datasets by overcoming challenges with repetitive sequences. This parallelized tool significantly speeds up homology searches, improving accuracy over existing methods.

Keywords:

Algorithms Bioinformatics Local alignments Parallel computing

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Searching large genomic datasets for local alignments presents significant computational challenges.
Repetitive sequences in genomic data increase runtime costs and complicate homology searches.
Effective filters are crucial for reducing search space without missing significant matches.

Purpose of the Study:

To introduce DREAM-Stellar, an updated, parallelized version of the Stellar local aligner.
To develop a sensitive and specific filter for practical homology searches in genomic data.
To compare DREAM-Stellar's performance against existing local alignment tools.

Main Methods:

DREAM-Stellar employs a four-step process: query/reference preprocessing, data structure building for query distribution, parallel computation, and result combination.
Utilizes the IBF data structure and a novel prefilter for efficient local alignment query distribution.
Performance evaluated on simulated and real genomic data against five other local aligners.

Main Results:

DREAM-Stellar demonstrates significant speed improvements, up to 900x faster than its predecessor on 32 threads.
It can identify all pairwise genome alignments within minutes, comparable in runtime to tools like BLAST.
Heuristic tools like BLAST may miss significant local alignments or be overwhelmed by less significant matches.

Conclusions:

DREAM-Stellar is a practical and fast tool for identifying local alignments in very long genomic sequences.
It is suitable for homology searches under the edit distance model.
The software is freely available for Linux and Mac OS X.