Bio-Data Science Training Program Faculty

 

Program Faculty

Student trainees will have the opportunity to work with a diverse group of mentors for their research rotations as well as their dissertations. The list of Departmental Affliations for our Program include (but are not limited to): The Departments of Biostatistics and Medical Informatics, Chemistry, Computer Sciences, Genetics, Oncology, and Virology. Many of our faculty are also members of the Center for Predictive Computational Phenotyping, a BD2K Center for Excellence (CPCP) as well as the Morgridge Institute for Research (MIR). Faculty trainers and their research interests are listed below.

 

Faculty Trainer Research Interests
Oncology (Molecular Virology)
 
Molecular mechanisms of viral replication, host interactions and oncogenesis
Biochemistry
 
Genetics of type 2 diabetes; gene causal networks and
diabetes
Cell and Regenerative Medicine
 
Multidisciplinary approaches to understand stem/progenitor cell function, blood cell development, and vascular biology
Biostatistics and Medical Informatics (Statistics)
 
Statistical problems in genetics, genomics; Development of improved methods for detecting & identifying genes contributing to variation in complex traits
Radiology (Biostatistics and Medical Informatics)
 
Use of computer techniques to improve the early detection of breast cancer; development of a Bayesian Network designed to assist radiologists in the post-discovery aspects of mammography
Chemistry (Biomolecular Chemistry)
 
Development and application of new technologies and
instrumentation for automated, large-scale whole protein characterization; links to expression
Biostatistics and Medical Informatics (Computer Sciences)
CPCP
 
Development and application of machine-learning algorithms in the context of biomedical, genomic problems
Biostatistics and Medical Informatics (Computer Sciences)
CPCP
 
Algorithms and statistical models for genomics; special
emphasis on RNA-Seq datasets
Computer Sciences
CPCP
 
Data integration, data/schema/ontology matching, information extraction, text management, building knowledge bases, and crowdsourcing
Genetics
 

Genomics of yeast responses to environmental stress and starvation; evolution of gene expression regulation, signal transduction & environmental interactions

Biostatistics and Medical Informatics (Computer Sciences, Morgridge Institute for Research)
 

Designing algorithms that leverage biological networks to connect different types of experimental data and detect surprising relationships among them; examining dynamic behaviors of biological networks and developing techniques to reconstruct dynamic models of signaling pathways and transcriptional regulatory networks from high-throughput proteomic and transcriptomic data.

Oncology (Genetics)
 

Molecular genetics of mammary carcinogenesis and translational research in the area of breast cancer prevention and therapy

Medicine - Geriatrics
CPCP
 

Early detection of Alzheimers Disease (AC) with multimodal imaging including amyloid imaging; Machine learning based multi-modal imaging markers of AD; Enriching clinical trials and improving trial design with multi-kernel machine learning to speed the discovery of effective treatments for AD; Caloric restriction effects of brain function and structure in non-human primates.

Biostatistics and Medical Informatics (Statistics)
CPCP
 

Statistical Genomics and Computational Biology; Statistical Computing; Statistical Inference with Censored Data

Christina Kendziorski

Biostatistics and Medical Informatics (Statistics)
CPCP
 

Development and application of statistical methods for gene mapping and gene expression studies in diseases (cancer; type 2 diabetes) using large RNA-Seq datasets

Statistics (Biostatistics and Medical Informatics)
CPCP
 

Development and application of statistical methods for biomedical research including on diseases (cancer; type 2 diabetes); computational problems are a focus

Biostatistics and Medical Informatics (Computer Sciences)
CPCP
 

Algorithms for data mining and machine learning, and their applications to biomedical data, especially clinical and high-throughput genetic and molecular data

Computer Sciences
CPCP
 
Big data management and analytics: invent and build technologies to manage and exploit the full potential of the ongoing big data revolution
Biostatistics and Medical Informatics (Statistics)
CPCP
 

Missing data in models for highly stratified or longitudinal data, generalized linear models, methods for behavior genetic designs and outcome-dependent sampling

Biostatistics and Medical Informatics (Computer Sciences, Wisconsin Institute for Discovery)
CPCP
 

Inference of structure and function of regulatory networks; comparative analysis of expression modules across species

Chemistry (Genetics)
 

Chemistry and biology of single molecule systems with applications to genomic sciences through bioinformatics pipelines dealing with large datasets; synthetic genomics

Biostatistics and Medical Informatics (Computer Sciences)
CPCP
 
Computer Vision and Biomedical Image Analysis
Chemistry
 

Development and application of novel methods and approaches for the analysis and manipulation of biomolecules; synthetic biology.

Medicine (Morgridge Institute for Research)
 

Examining the transcriptional networks in ES cells; Improving methods for generating human iPS cells, and correcting genetic defects in iPS cells; Developing new strategies to convert human pluripotent stem and somatic cells into hematopoietic, vascular, and cardiac progenitor cells; Understanding clocking mechanisms that control developmental rates.

Biostatistics and Medical Informatics (Statistics)
 

High-dimensional data analysis, variable selection and model selection, survival analysis, longitudinal data analysis, bioinformatics, machine learning and data-mining, statistical modeling.

Statistics (Morgridge Institute for Research)
CPCP
 

High-dimensional data, or highly unstructured data derived from many different sources (e.g., clinical trials, genetic sequencing and research experiments).