ReviewBiomolecules2024
The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction.
Review in Biomolecules, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Article
- Designing potent and immunogenic epitope based peptide vaccine against all serotypes of DENV via structural, physico-chemical and immunoinformatics-based approaches.Scientific reports · 2026Article
- Clustering-based progressive alignment with fuzzy logic (CPA-FL).Biochemistry and biophysics reports · 2026Article
- Interrelational Proteomic Sequence Features Enhance Predictive Modeling: Application to COVID-19 Severity.Biomedicines · 2026Article
- In Silico Design and Characterization of a Rationally Engineered Cas12j2 Gene Editing System for the Treatment of HPV-Associated Cancers.International journal of molecular sciences · 2026Article
- BridgeNet: a high-efficiency framework integrating sequence and structure for protein and enzyme function prediction.Briefings in bioinformatics · 2025Article
- AI-driven discovery of novel extracellular matrix biomarkers in pelvic organ prolapse.PLoS computational biology · 2025Article
- Article
- Selective Modulation of PAR-2-Driven Inflammatory Pathways by Oleocanthal: Attenuation of TNF-α and Calcium Dysregulation in Colorectal Cancer Models.International journal of molecular sciences · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Multiple sequence alignment (MSA) has evolved into a fundamental tool in the biological sciences, playing a pivotal role in predicting molecular structures and functions. With broad applications in protein and nucleic acid modeling, MSAs continue to underpin advancements across a range of disciplines. MSAs are not only foundational for traditional sequence comparison techniques but also increasingly important in the context of artificial intelligence (AI)-driven advancements. Recent breakthroughs in AI, particularly in protein and nucleic acid structure prediction, rely heavily on the accuracy and efficiency of MSAs to enhance remote homology detection and guide spatial restraints. This review traces the historical evolution of MSA, highlighting its significance in molecular structure and function prediction. We cover the methodologies used for protein monomers, protein complexes, and RNA, while also exploring emerging AI-based alternatives, such as protein language models, as complementary or replacement approaches to traditional MSAs in application tasks. By discussing the strengths, limitations, and applications of these methods, this review aims to provide researchers with valuable insights into MSA's evolving role, equipping them to make informed decisions in structural prediction research.
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Registered trials
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.