ArticleJournal of mathematical biology2014
Robust k-mer frequency estimation using gapped k-mers.
Article in Journal of mathematical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 62 citations in OpenAlex.
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- The effect of taxonomic, host-dependent features and sample bias on virus host prediction using machine learning and short sequence k-mers.Scientific reports · 2025Article
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- Non-local modeling of enhancer-promoter interactions, a correspondence on "LOCO-EPI: Leave-one-chromosome-out (LOCO) as a benchmarking paradigm for deep learning based prediction of enhancer-promoter interactions".Applied intelligence (Dordrecht, Netherlands) · 2025Article
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- Gapped-kmer sequence modeling robustly identifies regulatory vocabularies and distal enhancers conserved between evolutionarily distant mammals.Nature communications · 2024Article
- Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer.Genome research · 2024Article
- MicroRNAs provide negative feedback and stability in gene regulatory network models of cell-state transitions.Frontiers in epigenetics and epigenomics · 2024Article
- Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases.Nature genetics · 2023Article
- A survey on algorithms to characterize transcription factor binding sites.Briefings in bioinformatics · 2023Review
- DeepmRNALoc: A Novel Predictor of Eukaryotic mRNA Subcellular Localization Based on Deep Learning.Molecules (Basel, Switzerland) · 2023Article
- GM-lncLoc: LncRNAs subcellular localization prediction based on graph neural network with meta-learning.BMC genomics · 2023Article
- Sketching and sampling approaches for fast and accurate long read classification.BMC bioinformatics · 2022Article
- Indicators of Successful Career Transitions from Physical Sciences and Engineering to Biomedical Research.Current genomics · 2021Article
- LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.International journal of molecular sciences · 2020Article
- Enhancer Predictions and Genome-Wide Regulatory Circuits.Annual review of genomics and human genetics · 2020Review
- iterb-PPse: Identification of transcriptional terminators in bacterial by incorporating nucleotide properties into PseKNC.PloS one · 2020Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.
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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.