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个人简介
Dr. Galagan’s research is focused on Systems Biology of microbial organisms, specficially Mycobacterium tuberculosis – the causative agent of tuberculosis – and the fungus Neurospora crassa. The Galagan Lab is an interdisciplinary group that combines computational biology, genomics, and experimental lab work. Specific interests and projects include:
• Using a genomics, computational modeling, and experimental systems-identification techniques to reconstruct the gene regulatory network of M. tuberculosis.
• Developing and experimentally validating computational models of microbial metabolism for M. tuberculosis and N. crassa.
• Using high-throughput sequencing and comparative sequence analysis to study the functional evolution of M. tuberculosis.
• Developing computational methods for genomic data analysis (including gene prediction, gene expression analysis, and polymorphism discovery)
• Developing experimental methods for microbial systems identification and analysis, drawing on electrical and mechanical systems identification methods
• Using a genomics, computational modeling, and experimental systems-identification techniques to reconstruct the gene regulatory network of M. tuberculosis.
• Developing and experimentally validating computational models of microbial metabolism for M. tuberculosis and N. crassa.
• Using high-throughput sequencing and comparative sequence analysis to study the functional evolution of M. tuberculosis.
• Developing computational methods for genomic data analysis (including gene prediction, gene expression analysis, and polymorphism discovery)
• Developing experimental methods for microbial systems identification and analysis, drawing on electrical and mechanical systems identification methods
研究兴趣
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Biomacromoleculesno. 11 (2023): 5027-5034
Víctor H Tierrafría,Claire Rioualen,Heladia Salgado,Paloma Lara,Socorro Gama-Castro,Patrick Lally,Laura Gómez-Romero,Pablo Peña-Loredo, Andrés G López-Almazo, Gabriel Alarcón-Carranza, Felipe Betancourt-Figueroa,Shirley Alquicira-Hernández,
ECS Meeting Abstractsno. 66 (2020): 3318-3318
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