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Updated: Sep 15, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Ultrafast and ultralarge multiple sequence alignments using TWILIGHT.

Yu-Hsiang Tseng¹, Sumit Walia¹, Yatish Turakhia¹

¹Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA 92093, United States.

Bioinformatics (Oxford, England)

|July 15, 2025

Summary

This summary is machine-generated.

TWILIGHT is a new bioinformatics tool that performs multiple sequence alignment (MSA) faster and more accurately than existing methods. It efficiently handles large datasets on modern hardware, setting a new standard for genomic data analysis.

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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The ITS2 Database

Published on: March 12, 2012

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Multiple sequence alignment (MSA) is crucial in bioinformatics.
Current MSA tools face challenges with large datasets due to high runtime and memory demands.
Existing tools do not fully utilize modern CPU and GPU parallelism.

Purpose of the Study:

Introduce TWILIGHT, a novel MSA tool.
Optimize MSA for speed, accuracy, scalability, and memory efficiency.
Enable high-throughput alignment of large biological sequence datasets.

Main Methods:

Developed TWILIGHT with innovative parallelization strategies.
Implemented memory-efficiency techniques for large-scale alignments.
Integrated both CPU and GPU support for enhanced performance.

Main Results:

TWILIGHT demonstrated superior speed and accuracy on challenging datasets.
Achieved alignment of 1 million RNASim sequences in 30 minutes with <16 GB memory.
Successfully aligned over 8 million SARS-CoV-2 sequences, a first for public data.

Conclusions:

TWILIGHT overcomes limitations of existing MSA tools for large-scale data.
Offers unprecedented scalability for genomic alignment and analysis.
Sets a new benchmark for high-throughput bioinformatics.