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Doctor of Philosophy in Interdisciplinary Studies: Concentration

University/Institute: University of Louisville (UofL)
Location: United States - Louisville
Focus: Bioinformatics
Recommended Undergraduate Degrees: Biology, Chemistry, Computer Science, Math/Statistics
Degree Offered: Ph.D/DSc (< 1 year)Ph.D/DSc (Major/Primary Degree)

Program Goals:

Competencies

The Bioinformatics Program strives to achieve the highest quality instruction, leading to recognition by potential employers of the UofL graduates. Thus, graduates will be well trained, technically competent and competitive with graduates from other programs.

Graduates will also be adept in principles of research including critical thinking, problem solving and analytical skills, obtaining general competencies in the areas of:
a) Basic cell/molecular biology including macromolecular structures, transcription, proteomics and metabolomics, and cellular function (concepts of systems biology)
b) Fundamental understanding of experimental design
c) Basic probability and statistics (theory and methods)
d) Basics of computer algorithms
e) Knowledge of different biological databases and search engines
f) Knowledge of the scope and utility of available informatics databases and tools.

The three focus areas are Biomedical and Natural Sciences, Computational Sciences, and Mathematics and Statistics. These areas encompass the research interests of faculty in participating departments and schools.

Mathematics and Statistics

The area of Mathematics and Statistics includes a thorough grounding and expertise in mathematical modeling and statistical analysis of complex data sets derived from biological systems. Statistical analysis encompasses optimal experimental design strategies, sample size, and; defining information content in complex noisy data sets as applied to biological data sets. Applied mathematics includes modeling strategies for understanding the kinetics of complex biochemical networks, probability distributions, graph theoretic approaches, and chaos and complexity theory. The ultimate goal of this focus area is to train students in methodologies used to identify statistically significant changes in biological processes in order to develop mathematical models to better understand these processes.


Graduates in this concentration will have specific expert competencies in the following:
a) Mathematical modeling
b) Data mining
c) Optimization
d) Numerical methods
e) Statistical inference
f) High throughput data analysis
g) Advanced statistical computing


Biomedical and Natural Sciences

The area of Biomedical and Natural Sciences is concerned with the application of informatics approaches in the biological sciences, which includes problems of data collection, reduction, analysis and modeling of diverse biological processes. Examples include: genetic information and flow through transcription and translation through to the metabolome; interaction of objects within these rich data sets (Systems Biology); population â??level interactions including ecology, symbiosis; organism level information exchange (e.g. hormonal signaling); and genomic composition and structure (including structural prediction, functional prediction).

Graduates in this concentration will have specific expert competencies in:
a) Understanding of biological complexity, including networks
b) Systems approaches to biological complexity and interaction
c) Analysis of macromolecular structures
d) Transcription networks
e) Proteome networks
f) Metabolome networks


Computational Sciences

In the area of Computational Sciences, the emphasis is on algorithm development, using existing mathematical models and learning appropriate languages for different tasks, development of data mining methods for automatic data analysis (e.g. in any â??omicsâ??); and, pattern recognition.

Graduates in this concentration will have specific expert competencies in the following:
a) Programming efficiency and optimization
b) Algorithmic design and analysis
c) Data mining techniques
d) Data design


Additional Information

Year Program Established: 2012
Scholarships/assistanceships may be available: Yes
Type of academic terms: Semester

Average number of applicants per year: 5
Average number of applicants accepted per year: 2
Average number of incoming students per year: 2
Average number of graduates per year: 0

Program URL: http://bioinformatics.louisville.edu/phd/
Syllabus URL: http://bioinformatics.louisville.edu/phd/

Contact Person: Eric Rouchka ( bioinf@louisville.edu )

Last updated: Apr 30, 2015

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