A5023716437- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Bayesian Modeling and Causal Inference
- Time Series Analysis and Forecasting
- Microbial Metabolic Engineering and Bioproduction
- Gene expression and cancer classification
- Advanced Proteomics Techniques and Applications
- Genetic factors in colorectal cancer
- Genetic and Kidney Cyst Diseases
- Plant Virus Research Studies
- Statistical Methods and Inference
- Machine Learning in Healthcare
- Bayesian Methods and Mixture Models
- Asthma and respiratory diseases
- Marine and coastal ecosystems
- Metabolism and Genetic Disorders
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Data Analysis with R
- Genetic Associations and Epidemiology
- Phonocardiography and Auscultation Techniques
- Single-cell and spatial transcriptomics
- Neurological diseases and metabolism
- Human Mobility and Location-Based Analysis
- Anomaly Detection Techniques and Applications
- Stochastic processes and statistical mechanics
University of Wisconsin–Madison
2015-2022
University of Pittsburgh
2012
ABSTRACT Herpes simplex virus 1 (HSV-1) causes recurrent mucocutaneous ulcers and is the leading cause of infectious blindness sporadic encephalitis in United States. HSV-1 has been shown to be highly recombinogenic; however, date, there no genome-wide analysis recombination. To address this, we generated 40 recombinants derived from two parental strains, OD4 CJ994. The OD4-CJ994 were sequenced using Illumina sequencing system, recombination breakpoints determined for each Bootscan program....
We present a novel method for obtaining concise and mathematically grounded description of multivariate differences between pair clinical datasets. Often data collected under similar circumstances reflect fundamentally different patterns. For example, information about patients undergoing treatments in intensive care units (ICUs), or within the same ICU during periods, may show systematically outcomes. In such circumstances, probability distributions induced by datasets would differ selected...
The task of spatial cluster detection involves finding regions where some property deviates from the norm or expected value. In a probabilistic setting this can be expressed as region event is significantly more likely than usual. Spatial interest in fields such biosurveillance, mining astronomical data, military surveillance, and analysis fMRI images. almost all applications we are interested both question whether exists if it exists, most accurate characterization cluster. We present...
Advances in systems biology have made clear the importance of network models for capturing knowledge about complex relationships gene regulation, metabolism, and cellular signaling. A common approach to uncovering biological networks involves performing perturbations on elements network, such as knockdown experiments, measuring how perturbation affects some reporter process under study. In this article, we develop context-specific nested effects (CSNEMs), an inferring that generalizes...