Bacterial DNA sequence compression models using artificial neural networks

DOI10.3390/E15093435zbMath1361.92006OpenAlexW2065504303WikidataQ111518074 ScholiaQ111518074MaRDI QIDQ280530

Armando J. Pinho, Manuel J. Duarte

Publication date: 10 May 2016

Published in: Entropy (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/e15093435

zbMATH Keywords

compressionMarkov modelsneural netsfinite-context models

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Measures of information, entropy (94A17) Genetics and epigenetics (92D10)

Uses Software

• PRMLT

Cites Work

• A new challenge for compression algorithms: Genetic sequences
• A universal algorithm for sequential data compression

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