Chemometrics for QSAR with low sequence homology: Mycobacterial promoter sequences recognition with 2D-RNA entropies

Predicting mycobacterial sequences promoter of protein synthesis is important in the study of protein metabolism regulation. This goal is however considered a challenging computational biology task due to low inter-sequences homology. Consequently, a previous work based only on DNA sequence had to u...

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Veröffentlicht in:	Chemometrics and intelligent laboratory systems 2007-01, Vol.85 (1), p.20-26
Hauptverfasser:	González-Díaz, Humberto, Pérez-Bello, Alcides, Cruz-Monteagudo, Maykel, González-Díaz, Yenny, Santana, Lourdes, Uriarte, Eugenio
Format:	Artikel
Sprache:	eng
Schlagworte:	Entropy Information theory Machine learning algorithms Markov models Mycobacterial promoter sequences Mycobacterium QSAR RNA secondary structure
Online-Zugang:	Volltext
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