Assistant Professor of Biomedical Informatics
Harvard Medical School
Dr. Farhat is an Assistant Professor of of
Biomedical Informatics atHarvard Medical School and a a practicing physician at
the Massachusetts General Hospital Division of Pulmonary and Critical Care
Medicine.
Dr. Farhat's research focuses on the development and application of methods for associating genotype and phenotype in infectious disease pathogens, with a strong emphasis on translation to better diagnostics and surveillance in resource-poor settings. Farhat's work has focused on bacterial and viral pathoges and spans the spectrum from computational analysis to field studies. She is PI and Co-Investigator on several large projects funded by NIH including the NIAID and the BD2K initiative.
Maha Farhat holds an MD from the McGill University Faculty of Medicine and a MSc in biostatistics from the Harvard Chan School of Public Health.
Assistant Professor of Biomedical Informatics
Harvard Medical School
Dr. Farhat is an Assistant Professor of of
Biomedical Informatics atHarvard Medical School and a a practicing physician at
the Massachusetts General Hospital Division of Pulmonary and Critical Care
Medicine.
Dr. Farhat's research focuses on the development and application of methods for associating genotype and phenotype in infectious disease pathogens, with a strong emphasis on translation to better diagnostics and surveillance in resource-poor settings. Farhat's work has focused on bacterial and viral pathoges and spans the spectrum from computational analysis to field studies. She is PI and Co-Investigator on several large projects funded by NIH including the NIAID and the BD2K initiative.
Maha Farhat holds an MD from the McGill University Faculty of Medicine and a MSc in biostatistics from the Harvard Chan School of Public Health.
Journal article
CONCLUSION: Our findings highlight the role of rifampicin plasma exposure in optimizing bacillary clearance and improving treatment outcomes, even within standard dosing regimens for drug-susceptible tuberculosis.
Journal article
In Mycobacterium tuberculosis, a prevalent and deadly pathogen, resistance to antibiotics evolves primarily through non-synonymous mutations in proteins. Sequence-based analyses are currently used to understand the genetic basis of antibiotic resistance, either via genotype-phenotype association, or via signals of convergent evolution. These methods focus on primary sequence and usually neglect other biological signals such as protein structural information. We hypothesize that integrating the...