Microbiology Ph.D.

Bioinformatics Specialty Program

Description and Purpose of Specialty

The emerging field of bioinformatics has promoted a close working relationship between researchers in the life sciences and the computational sciences. The possible uses of bioinformatic technology in the microbiology field are immense. At The University of Iowa, many researchers in the Microbiology Department are now using bioinformatics to address questions such as how various microbes alter overall gene expression profiles in host cells, how microbes themselves alter their own gene expression in response to different stimuli and growth conditions, and how various pathogens affect expression of immune response pathways. It has become clear that the availability of more intense bioinformatic training is necessary for meeting the needs of microbiology students interested in bioinformatics. With the recently developed Center for Bioinformatics and Computational Biology at The University of Iowa (http://genome.uiowa.edu), this has now become a possibility. We have therefore initiated a formal specialty within the Microbiology Ph.D. program that will lead to a Ph.D. in Microbiology.

The goals of the Bioinformatics Specialty Program will be two-fold:

  1. Offer a Microbiology Ph.D. training program involving coursework and Ph.D. thesis research opportunities in bioinformatics and microbiology for those incoming students who already have an interest in computational/computer sciences that would like to apply these interests and skills to microbiology-related topics.
  2. Provide students with microbiology/life sciences backgrounds exposure and training in bioinformatics.

Coursework

Students will be required to meet a minimum 22 semester hour graduate course requirement. This will include the 15 semester hours already required for Microbiology graduate students plus 7 additional hours in bioinformatics classes (see below). As with current policy, it will be up to the discretion of the student's thesis committee to determine whether additional classes should be taken to make up for certain deficits or enhance training in a specific field. All students in the bioinformatics specialty, regardless of their original discipline, will be required to master (1) a subdiscipline of Microbiology (e.g. Virology, Pathogenesis, Immunology, Microbial Genetics) (2) and Bioinformatics Tools and Applications. It will also be expected that students will have taken courses in computing and statistics. These requirements can be met by either enrolling in upper level undergraduate courses prior to matriculation (e.g. as an undergraduate) or by enrolling in a combination of undergraduate and graduate courses selected to address individual student needs after matriculation as a graduate student.

1. Microbiology and Interdisciplinary Courses in Life Sciences

- Same as those already approved and listed in Graduate Student Handbook.

See http://www.uiowa.edu/registrar/catalog/CarverCollegeofMedicine/Microbiology.html

2. Computing

Examples of courses offered at UI:

  • Practical Computer Science (22C:104, first offering: Fall '03)
  • Fluency in at least one programming language (Examples: Java (55:033) or C++ (22c:112))

3. Statistics (at least one semester equivalent)

Examples of courses offered at UI:

  • Biostatistics (22S:101 or equivalent). Offered by Statistics and Actuarial Science
  • Introduction to Biostatistics (171:161). Offered by College of Public Health

4. Bioinformatics Tools and Applications

Examples of courses offered at UI: Two courses will be required, the nature of which would depend upon interest and level of expertise when entering the program.

  • Bioinformatics I: Introduction to Bioinformatics (127:170; same as 2:170; 55:122)
  • Bioinformatics II: Techniques and Tools (51:123)
  • Bioinformatics III: Computational Genomics (127:173; same as 2:174, 51:122 and 55:122)
  • Bioinformatics IV: Statistics of Bioinformatics
 

Research Training: The research training envisioned for Bioinformatics Specialty students is modeled after the program followed by students in the traditional Microbiology track, with modifications as noted.

Rotations: The policies on rotations will be similar to those of the Microbiology Department. Specifically, all students will be required to rotate among three laboratories during their first year in graduate school. The choice of laboratories will be determined by the student in consultation with the Graduate Advisory Committee and is subject to approval by the head of the laboratory. One rotation must be done in a laboratory outside the department that offers focused experience in bioinformatics (see member list at http://genome.uiowa.edu). It is anticipated that the head of this lab will serve as the student's co-mentor (see below) but will not serve as the student's main research mentor.

Choosing a Mentor/Co-mentor

For students in the Bioinfomatics Specialty, both a mentor and co-mentor will be chosen representing the computational and biological aspects of the research project. The dual mentor system is meant to formally tie together the experimental and computational aspects of the Ph.D. thesis project. The co-mentor will be a member of the student's comprehensive and thesis committee. Three members of the Comprehensive Examination Committee must be from Microbiology and the Committee Chair must be from Microbiology. At least two members must be part of the current Bioinformatics Program on campus (http://genome.uiowa.edu). Since a faculty member may represent both subdisciplines, the fifth member can be from outside both disciplines. At least one member must be from outside the Department of Microbiology.

A list of potential mentors from Microbiology is given below:

Michael A. Apicella Gail A. Bishop Al J. Klingelhutz
Wendy J. Maury Linda L. McCarter Mark F. Stinski
Jerrold P. Weiss Mary E. Wilson  

Course descriptions

Computing

22C:104 Practical Computer Science (3sh) This first course is an overview of computing principles and fundamental aspects of computer science for the nonspecialist. Topics covered are the history of computing, basic computer architecture and operating system concepts, fundamentals of relational databases, and elementary algorithmic ideas. Introduction to computer programming in Perl, including variables, control structures, file I/O, regular expressions, objects and built-in functions.

Fluency in at least one programming language (e.g. Java (55:033) or C++ (22C:112))

Statistics

22S:101 Biostatistics (3 sh) Statistical methods primarily for research in health sciences and related fields; descriptive statistics, estimation, test of hypotheses.

171:161 Introduction to Biostatistics (3 sh) Statistical methods for research in public health sciences.

Bioinformatics Tools and Applications

127:170 Introduction to Bioinformatics (Bioinformatics I) (same as 2:170; 55:121) (4 sh, Fall). Overview of bioinformatics and genome science including genome projects, functional genomics, phylogenetics, proteomics, microarrays, DNA polymorphisms and data mining algorithms. Basics of genetics and molecular biology will be presented at the outset to allow students of all disciplines to participate. Experimental methods and analytical approaches will be discussed side by side. Two lecture hours plus 2 workshop hours weekly. Suitable for upper level undergraduates and graduate students new to the subject.

51:123 Bioinformatics Techniques and Tools (Bioinformatics II) (3 sh, Fall). Introduction to the tools and techniques needed to address computational problems in Bioinformatics, Computational Biology and Genomics. Emphasis will be on programming, algorithms, databases and the design and implementation of systems and applications to solve problems in these areas.

127:173 Computational Genomics (Bioinformatics III) (cross-listed as 2:174, 51:122, 55:122) (3 sh, Spring). An introduction to contemporary computational methods used in genomics and molecular biology. Major topics include DNA and RNA sequence analysis, sequence/gene/disease mapping, gene expression and disease gene linkage. The course consists of in-depth coverage of principal genome science challenges, and their most recent "solutions". (This course is cross-listed as 2:174 in Biology and 55/51:122 in Engineering).

Statistics of Bioinformatics (Bioinformatics IV) (3sh, Spring). Overview of statistical methods and applications pertinent to bioinformatics and related fields. Topics covered will include basic probability and statistics theory; algorithms, scoring and statistical significance of pair wise and multiple sequence alignments and databases searching; models and statistical significance in gene finding; protein family prediction; analysis of microarray data.