Bioinformatics
Investigators
- Cho, HyungJun,
PhD Dr. Cho has worked on statistical research in
medical and biological data. He has applied and developed many computational and
statistical techniques for various problems in biological and medical studies.
Dr. Cho's current interest is in statistical and computational analysis of
high-throughput genomic and proteomic data.
- French, Brent A., PhD. Dr. French's laboratory works
at the interface between molecular biology, cardiovascular science and
biomedical engineering. An interdisciplinary approach is used to integrate
recent technical advances in bioengineering with basic research in the area of
ischemic heart disease. Specifically, this research employs cutting-edge imaging
techniques such as cardiac MRI to provide accurate assessments of the efficacy
of novel therapeutic approaches against myocardial infarction and heart failure.
Current research projects in the laboratory also use molecular techniques to
characterize the role of inflammation in myocardial infarction and heart
failure. Recent work shows that the biological messenger nitric oxide plays a
multifunctional role in protecting the heart against ischemic damage. Thus one
project seeks to elucidate the diverse functions of nitric oxide during and
after ischemia / reperfusion injury to the heart. For example, molecular
techniques are now being used to correlate changes in NOS gene expression with
in vivo functional changes in the heart as measured by cardiac MRI.
- Johnson, Michael., PhD. Dr. Johnson has a
Ph.D. in biophysics with a specialty in modeling of biological processes. Dr.
Johnson has authored more than 208 publications and edited 8 books, the majority
of which involve mathematical modeling of biological processes (particularly
numerical computer methods and quantitative neuroendocrinology).
- Knaus, William A., MD. Secure Digital Record Repository
for Virginia (SDRRV)- SDRRV's objective is to create a secure record repository
utility across the state that will combine biologic, clinical, demographic,
environmental, and outcomes data. SDRRV will address the fundamental scientific
questions of how multi-dimensional and multi-source data can be integrated in a
manner that engenders the trust of Virginia's citizens with respect to
protection of individual biologic and related personal and social information.
The SDRRV will also be designed to enable institutions across the state to
efficiently meet the new HIPAA (Health Insurance Portability and Accountability
Act) requirements while broadening their abilities to use and integrate data for
a variety of scientific research and public policy purposes with primary
attention to ethical principles and civil rights. The SDRRV will use a computer
science/systems engineering approach to design integration, optimize
functionality, and create efficient human-computer interfaces. SDDRV will
initially identify the types and sources of new biologic and genetic data and
the variety of existing and proposed methods and tools designed for their
interpretation. A detailed examination of the logistic, technical, legal,
scientific, and political challenges encountered in collecting, storing,
interpreting, and integrating these data with existing electronic sources of
clinical, demographic, environmental, public health, and outcomes information
will be completed. Then, in an open-architecture, academic, industry,
government, and citizen-endorsed effort, SDRRV will implement a working
prototype and pilot of a digital record based repository. The prototype will
involve a minimum of seven major research-based Virginia Universities, the
state's Department of Health, the state Legislature and Governor's Office, three
integrated health systems, a local community-oriented partnership association,
citizen based privacy protection and health care advocacy groups along with
representatives from related information and biotechnology based industries.
This prototype will encompass a minimum of 50 % of Virginia's population. Data
integration will be accomplished by creating a computed grid distributed network
among primary information sources linked to specific data-intensive computing
applications, methods, and tools in a open source community.
- Kovatchev, Boris P., PhD. Dr. Kovatchev has 10 years
experience in biomathematics. He has had continuous NIH funding since 1996
exclusively dedicated to biomathematical modeling for diabetes research. He has
developed the low blood glucose index, the best predictor to date of severe
hypoglycemia, created the theory of risk analysis of blood glucose data,
developed new computational tools for assessment of behavioral irregularity
associated with type 1 diabetes and for assessment of long-term diabetes
control, and successfully developed a remarkably accurate deterministic model of
insulin-glucose dynamics. Two patent disclosures have been filed and licensed by
industry leaders in the area of diabetes management.
- Lee, Jae K., PhD. Dr. Lee has worked on statistical
research in genetic population inference, DNA structure analysis,
high-throughput gene chip data analysis, and linkage association study for human
genetic diseases. He has applied and developed many computational &
statistical techniques for various problems in molecular biology and cancer
genetics, such as anticancer gene-drug discovery on high throughput gene
expression data and linkage association study for identifying quantitative trait
loci of pedigree data. Dr. Lee's current interest is in the analysis and
genome-wide information integration of microarray gene expression data. (Dr. Lee's Departmental Web page)
- Ley, Klaus F., M.D. Affemetrix Gene Chip analysis on
CD8+ T cells (completed) and mouse neutrophils (in progress) Maintain website on
leukocyte adhesion molecules at http://hsc.Virginia.EDU/medicine/basic-sci/biomed/ley/
Interested in pathways/ annotation/curated databases
- Lyman, Jason A., M.D., M.S. Dr. Lyman's research
interests include physician order entry, data warehousing, informatics
education, data modeling, clinical terminologies, and the application of
standards in clinical informatics. In addition to other projects, he has been
heavily involved in the collaborative efforts between UVa's HES and Systems
Engineering departments to explore the potential for multi-institutional
approaches to the integration of clinical, biological, and demographic
data.
- Pearson, William., PhD. Sequences (mostly
protein, some DNA) -Sequence/structure relations -Distant homology -Distribution
in protein space (is folding easy or hard) -Genome sequences Evolutionary
constraints -Functional Predictions from rate analysis -Comparative genomics-are
conserved non-coding sequences functional? Genome-Scale data and genome
databases -How to integrate quantitative sequences/evolutionary information with
qualitative functional information -Displaying information on a genome
scale.
- Peddada, Shayamal D., PhD. Working on several
different problems. An example of my research is to develop methods for
analyzing time-course and dose-response microarray experiments. I am developing
order-restricted inference based procedures for analyzing such data.
- Pelletier, Sandra., PhD. I received my PhD in
biochemistry studying the relationship between protein structure and function in
G-protein coupled receptors and did my and postdoctoral training in cell biology
researching the entry of influenza virus into host cells. My current position as
Assistant Professor of Research in the Department of Health Evaluation Sciences
allows me to apply these basic research foundations to clinical care, thus
contributing to the bridging of basic and clinical research. My interests
include database design, data integration, knowledge representation / ontology
and the conceptual development of analyses and methods that utilize clinical
data, existing knowledge resources and informatics to further discovery
research, clinical diagnostics and the targeting of therapeutics. Knowledge
resources of interest include both genomic and proteomic databases. But, I am
particularly interested in using knowledge resources related to protein
structure, function and interactions (e.g. signal transduction pathways) and
those from model organisms to understand complex multifactorial conditions such
as cancer and diabetes. Current projects include the integration of patient
specific `biological' data (genetic (mutations, gene expression), proteomic
profiling) and family health history data into the electronic patient record and
the development of methods for analyses that utilize these resources. I also
direct my attention to teaching efforts here in the department that address the
utilization of genomic, proteomic and knowledge resources as well as science and
health education for consumers (e.g. individuals health risks and health
practices, middle school kids).
- Skalak, Thomas C., PhD. We are very interested in a
future hire of a faculty member in the area of computational
biology-probably-integrative modeling of gene protein circuitry or tissue
assembly/remodeling/functionality. We would probably not overlap BME hire in the
existing areas of gene sequence homology searching or annotation. My own lab is
working on computational automata for predicative modeling of vascular assembly
and patterning in mammals, and also applications to developmental processes
during early mophogenesis in xenopus.
Courses related to Bioinformatics
in UVa
- Core Graduate Biochemistry Course (Bioch/BIMS 503) : William Pearson Macromolecular Structure
and Function-approx. 6 lectures on protein sequence comparison, secondary
structure prediction, structure comparison, domain databases
- Computer Analysis of DNA and Protein sequences (Bioch 508) (every
other year): William Pearson
- Biomedical Applications of Genetic Engineering (BIOM 706) (Spring
'03: MW 12:00-1:15): Brent A. French This course provides biomedical
engineers with a grounding in molecular biology and a working knowledge of
recombinant DNA technology, thus establishing a basis for the evaluation and
application of genetic engineering in whole animal systems. Beginning with the
basic principles of genetics, this course examines the use of molecular methods
to study gene expression and its critical role in health and disease. Topics
include DNA replication, transcription, translation, recombinant DNA
methodology, methods for analyzing gene expression (including microarray and
genechip analysis), methods for creating genetically-engineered mice, and
methods for accomplishing gene therapy by direct in vivo gene
transfer.
- Statistical Computing and Graphics (HES 703/STAT 301/STAT
501): Frank E. Harrell Jr Topics include the S language
for statistical computing, theory and application of statistical graphics,
exploratory data analysis. Taught each fall. Syllabus:
http://hesweb1.med.virginia.edu/biostat/ teaching/statcomp.
- STAT 731: Advanced Data Analysis: Frank E. Harrell Jr Advanced use of the bootstrap
and multiple imputation in statistical modeling, spline surfaces, penalized
maximum likelihood estimation, data reduction, and ordinal response models.
Taught every other spring. Syllabus: http:
//hesweb1.med.virginia.edu/biostat/teaching/biostat.mod.
- Comprehensive Introduction to Clinical Investigation (CI2):
William A. Knaus One-month executive training
program for medical residents, providing overview of modern biology, genetics,
and information management.
- Statistical Bioinformatics in Medcine (HES795) (Spring `03: MW
11-12:15):Jae K. Lee Dr. Lee teaches Statistical
Bioinformatics in Medcine (HES795) (Spring `03: MW 11-12:15). This course is
designed for wide range of students with basic concepts in statistics. Several
important topics in Bioinformatics and computational biology will be discussed,
including gene expression data analysis, statistical discovery of differential
expression, clustering and classification, hierarchical modeling, and linkage
analysis.
(http://hesweb1.med.virginia.edu/biostat/teaching/statbio/index.html)
- (HES-745, Fall MW 1-2:15). Jason A. Lyman This course is intended for
students interested in learning basic database concepts, including relational
DBMS's, SQL, data modeling, and normalization.
- Introduction to Health Informatics, (HES-707, Fall WF
8:30-9:45): Jason A. Lyman This is a survey course with
topics that include information processing and management, clinical decision
support, computer-based patient records, standards and coding, and
databases.
Seminars and Special Lectures
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