Evidence map›Paper›PMID 42909599›Full record

ArticleAnalytical and bioanalytical chemistry2026

APV-Sankey: a k-mer persistence visualization tool for HT-SELEX data analysis to identify aptamer candidates.

Yu Zhang, Yashan Wang, Yajing Gao, Keyi Hu, Hao Gong, Haijing Jia, Xin Zhang, Xinhui Lou

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Article in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Yu Zhang *Department of Chemistry, Capital Normal University, Beijing, 100048, China.
Yashan Wang *Honours College of Capital Normal University, Capital Normal University, Beijing, 100048, China.
Yajing GaoDepartment of Chemistry, Capital Normal University, Beijing, 100048, China.
Keyi HuDepartment of Chemistry, Capital Normal University, Beijing, 100048, China.
Hao GongDepartment of Chemistry, Capital Normal University, Beijing, 100048, China.
Haijing JiaDepartment of Chemistry, Capital Normal University, Beijing, 100048, China.
Xin ZhangDepartment of Chemistry, Capital Normal University, Beijing, 100048, China. xinzhang@cnu.edu.cn.ORCID http://orcid.org/0000-0002-6040-8257
Xinhui LouDepartment of Chemistry, Capital Normal University, Beijing, 100048, China. xinhuilou@cnu.edu.cn.

Funding

Beijing Outstanding Talents Training Fund for Youth Backbone Individual Project 2017000020124G081Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds KM201910028014National Natural Science Foundation of China 21705112National Natural Science Foundation of China 22374104
6 · The paper itself

Abstract

APV-Sankey is a novel visualization and analysis tool for High-Throughput Systematic Evolution of Ligands by Exponential Enrichment (HT-SELEX) data. By tracking k-mer persistence and concatenation across SELEX rounds via Sankey diagrams, APV-Sankey provides a complementary framework for identifying aptamer candidates, assessing SELEX progression, and facilitating the interpretation of HT-SELEX data. We demonstrate that k-mer persistence analysis captures biologically relevant patterns in SELEX evolution, complementing existing approaches based on sequence abundance. We benchmark APV-Sankey against standard metrics including final-round abundance, fold enrichment, and k-mer frequency, showing that persistence provides an orthogonal ranking dimension (Spearman ρ = - 0.192 with abundance) with 90% of top-200 persistent k-mers unique to the persistence ranking. APV-Sankey generates structured, round-annotated k-mer datasets suitable for downstream deep learning applications in aptamer binding prediction, positioning it as a data analysis platform for in silico aptamer research.

Indexed as

AptamerBioinformatics toolHT-SELEXK-mer analysisSankey diagramVisualization

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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.