Journal article
AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers
Molecular therapy. Nucleic acids, Vol.35(4), 102358
12/2024
DOI: 10.1016/j.omtn.2024.102358
PMCID: PMC11539416
PMID: 39507401
Abstract
Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.
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Thiel and colleagues highlight an aptamer clustering algorithm, AptamerRunner. AptamerRunner allows for efficient analysis and visualization of aptamers using advanced clustering techniques that incorporate sequence and structure relatedness. Integration of clustering results with ranking data provides a comprehensive interpretation clustering results, aiding in the identification of optimal aptamer candidates.
Details
- Title: Subtitle
- AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers
- Creators
- Dario Ruiz-Ciancio - University of Iowa, Internal MedicineSuresh Veeramani - University of Iowa, Hematology, Oncology, and Blood & Marrow TransplantationRahul Singh - University of IowaEric Embree - Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USAChris Ortman - University of IowaKristina W. Thiel - University of IowaWilliam H. Thiel - Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Molecular therapy. Nucleic acids, Vol.35(4), 102358
- DOI
- 10.1016/j.omtn.2024.102358
- PMID
- 39507401
- PMCID
- PMC11539416
- NLM abbreviation
- Mol Ther Nucleic Acids
- ISSN
- 2162-2531
- eISSN
- 2162-2531
- Publisher
- Elsevier Inc
- Grant note
- American Heart Association scientist development grant: 14SDG18850071 National Institutes of Health: R01HL139581, R01HL157956, K22CA263783 National Science Foundation: IIS-1817239 Department of Defense: DOD CDMRP-PRCRP CA220729 American Cancer Society: IRG-18-165-43 Bunge and Born Fund: FBB-20170609 Fulbright-Argentinean Ministry of Education: ME-FLB-2022-2023
This work was supported by an American Heart Association scientist development grant (14SDG18850071 to W.H.T.) , the National Institutes of Health (R01HL139581 and R01HL157956 to W.H.T.; K22CA263783 to K.W.T.) , the National Science Foundation (IIS-1817239 to R.S.) , the Department of Defense (DOD CDMRP-PRCRP CA220729 to K.W.T.) , the American Cancer Society (HCCC, IRG-18-165-43 to S.V.) , the Bunge and Born Fund (FBB-20170609 to D.R.C.) , and the Fulbright-Argentinean Ministry of Education (ME-FLB-2022-2023 to D.R.C.) .
- Language
- English
- Electronic publication date
- 10/2024
- Date published
- 12/2024
- Academic Unit
- Hematology, Oncology, and Blood & Marrow Transplantation; Cardiovascular Medicine; Obstetrics and Gynecology; Computer Science; Internal Medicine
- Record Identifier
- 9984732541702771
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