Evidence map›Paper›PMID 41254499›Full record

ArticleBMC bioinformatics2025

SeqForge: a scalable platform for alignment-based searches, motif detection, and sequence curation across meta/genomic datasets.

Elijah R Bring Horvath, Jaclyn M Winter

Abstract read
In one paragraph

Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. An extremophilicbioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Elijah R Bring HorvathDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, 84112, USA. eli.bringhorvath@pharm.utah.edu.
Jaclyn M WinterDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, 84112, USA. jaclyn.winter@utah.edu.

Funding

Genomics-Assisted Antibiotic Discovery from Unprecedented Microbes of the Great Salt LakeR01AI155694 · NIAID · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI WINTER, JACLYN MARIE · 2021 to 2025
$3.1M
NIAID NIH HHS R01 AI155694NIH HHS 1R01AI155694
6 · The paper itself

Abstract

backgroundThe rapid increase in publicly available microbial and metagenomic data has created a growing demand for tools that can efficiently perform custom large-scale comparative searches and functional annotation. While BLAST + remains the standard for sequence similarity searches, population-level studies often require custom scripting and manual curation of results, which can present barriers for many researchers.

resultsWe developed SeqForge, a scalable, modular command-line toolkit that streamlines alignment-based searches and motif mining across large genomic datasets. SeqForge automates BLAST + database creation and querying, integrates amino acid motif discovery, enables sequence and contig extraction, and curates results into structured, easily parsed formats. The platform supports diverse input formats, parallelized execution for high-performance computing environments, and built-in visualization tools. Benchmarking demonstrates that SeqForge achieves near-linear runtime scaling for computationally intensive modules while maintaining modest memory usage.

conclusionsSeqForge lowers the computational barrier for large-scale meta/genomic exploration, enabling researchers to perform population-scale BLAST searches, motif detection, and sequence curation without custom scripting. The toolkit is freely available and platform-independent, making it suitable for both personal workstations and high-performance computing environments.

Indexed as

Computational BiologyDatabases, GeneticMetagenomicsSoftwareSequence AlignmentBioinformaticsBLASTGenome miningGenomicsMetagenomicsMicrobes

Identifiers

PMID41254499
PMCPMC12625553

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.