ArticleScientific reports2013
Applying Shannon's information theory to bacterial and phage genomes and metagenomes.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- How Does Genetic Information Enable Life?Bulletin of mathematical biology · 2026Article
- The Gut Microbiome in Autosomal Dominant Polycystic Kidney Disease: A Cross-Sectional Study.Kidney360 · 2025Article
- From nucleotides to numbers: a comprehensive review of RNA feature extraction methods for computational modelling.Briefings in bioinformatics · 2025Review
- Informational rescaling of PCA maps with application to genetic distance.Computational and structural biotechnology journal · 2025Article
- Information Theory for Biological Sequence Classification: A Novel Feature Extraction Technique Based on Tsallis Entropy.Entropy (Basel, Switzerland) · 2022Article
- MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors.Briefings in bioinformatics · 2022Article
- Information Entropy in Chemistry: An Overview.Entropy (Basel, Switzerland) · 2021Review
- Shannon entropy as a metric for conditional gene expression in Neurospora crassa.G3 (Bethesda, Md.) · 2021Article
- Rapid discovery of novel prophages using biological feature engineering and machine learning.NAR genomics and bioinformatics · 2021Article
- Similarity Studies of Corona Viruses through Chaos Game Representation.Computational molecular bioscience · 2020Article
- Article
- Relationship between digital information and thermodynamic stability in bacterial genomes.EURASIP journal on bioinformatics & systems biology · 2016Article
- Review
- Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification.Bioinformatics (Oxford, England) · 2015Article
- Hepatitis C Virus (HCV) NS3 sequence diversity and antiviral resistance-associated variant frequency in HCV/HIV coinfection.Antimicrobial agents and chemotherapy · 2014Article
- A virulent strain of deformed wing virus (DWV) of honeybees (Apis mellifera) prevails after Varroa destructor-mediated, or in vitro, transmission.PLoS pathogens · 2014Article
- Information theory applications for biological sequence analysis.Briefings in bioinformatics · 2014Review
- Information measure for long-range correlated sequences: the case of the 24 human chromosomes.Scientific reports · 2013Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
All sequence data contain inherent information that can be measured by Shannon's uncertainty theory. Such measurement is valuable in evaluating large data sets, such as metagenomic libraries, to prioritize their analysis and annotation, thus saving computational resources. Here, Shannon's index of complete phage and bacterial genomes was examined. The information content of a genome was found to be highly dependent on the genome length, GC content, and sequence word size. In metagenomic sequences, the amount of information correlated with the number of matches found by comparison to sequence databases. A sequence with more information (higher uncertainty) has a higher probability of being significantly similar to other sequences in the database. Measuring uncertainty may be used for rapid screening for sequences with matches in available database, prioritizing computational resources, and indicating which sequences with no known similarities are likely to be important for more detailed analysis.
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