A5045042673- Bioinformatics and Genomic Networks
- Computational Drug Discovery Methods
- Gene expression and cancer classification
- Machine Learning in Bioinformatics
- Explainable Artificial Intelligence (XAI)
- Bartonella species infections research
- Cytomegalovirus and herpesvirus research
- Herpesvirus Infections and Treatments
- Genetic Associations and Epidemiology
University of Arizona
2018-2020
Eugene Applebaum College of Pharmacy and Health Sciences
2019
Wayne State University
2019
In the USA, nearly one in three people will experience herpes zoster (HZ) their lifetime. Underserved communities may be at even higher risk due to several factors, including access healthcare, education, and co-morbid conditions. The purpose of this study was investigate current knowledge, attitudes, beliefs practices (KABP) relative HZ vaccines a large urban city. A cross-sectional KABP survey conducted via in-person interview among 381 participants aged ≥ 50 years Detroit, MI, from June...
Forty-two percent of patients experience disease comorbidity, contributing substantially to mortality rates and increased healthcare costs. Yet, the possibility underlying shared mechanisms for diseases remains not well established, few studies have confirmed their molecular predictions with clinical datasets. In this work, we integrated genome-wide association study (GWAS) associating single nucleotide polymorphisms (SNPs) transcript regulatory activity from expression quantitative trait...
Abstract Background In this era of data science-driven bioinformatics, machine learning research has focused on feature selection as users want more interpretation and post-hoc analyses for biomarker detection. However, when there are features (i.e., transcript) than samples mice or human samples) in a study, poses major statistical challenges detection tasks traditional techniques underpowered high dimension. Second third order interactions these pose substantial combinatoric dimensional...
Abstract Background In this era of data science-driven bioinformatics, machine learning research has focused on feature selection as users want more interpretation and post-hoc analyses for biomarker detection. However, when there are features (i.e., transcripts) than samples mice or human samples) in a study, it poses major statistical challenges detection tasks traditional techniques underpowered high dimension. Second third order interactions these pose substantial combinatoric...