The University of Toledo

MASTERS PROGRAM IN BPG                           

ADMISSION REQUIREMENTS
Applicants to the MSBS degree with a concentration in  Bioinformatics, Proteomics and Genomics must meet the following requirements, in addition to those of the UTHSC Graduate School:

1. Earned bachelor’s degree or earned graduate degree from an accredited college or university. Applicants with a degree in progress will be considered.

2. GPA of 3.0 or above.  GPA of 2.5 or above, may apply for provisional acceptance that would change to Regular (non-probationary) status, if their first term graduate coursework has a GPA of 3.0 or above (4-point scale). 

3. Minimum GRE composite score of 300 (combined verbal and quantitative) and 3.5 (analytical). GRE scores are required and they must be current (within the last five years).  The GRE is not required if you have MCAT scores as an alternative (taken by medical science and MD/PhD Program applicants as national equivalent).   

4. Official transcripts for undergraduate and any graduate education.

5. Three letters of recommendation from college faculty or research supervisors

6. Completed online application form, at http://apply.utoledo.edu, and accompanying application fee (or waiver) *

7. TOEFL scores for applicants whose native language is not English.  We require a score of 550 or higher for the paper-administered version, 213 or higher for the computer-administered version, and 80 or higher for the Internet-administered version. IELTS scores are accepted in place of TOEFL (6.5 or higher). However, beginning with Spring 2014 admissions, IELTS will no longer be accepted.

Previous research experience is considered, but not required.  Students can begin at the start of any term, though Fall entry is recommended.  Admissions are made on a rolling basis until the class is filled. There is no fixed deadline. 

* Students who have already applied to the Program can check their application status online at this link http://application.utoledo.edu.  If a student's application is incomplete, this site will indicate which documents are missing.

 
Click here for BPG MSBS COURSE SCHEDULE (in full PDF format ) OR  Click here for HTML format.

Information for International Students can be found here: http://www.utoledo.edu/graduate/prospectivestudents/admission/guidelines.html

 
GRADUATE STUDENT TRAVEL SUPPORT -  Please see Graduate Studies Handbook at this link:
http://www.utoledo.edu/graduate/hsc/hsc_handbook10/FinancialSupport.html 

SELECTING A MAJOR ADVISOR AND RESEARCH PROJECT
1) Before selecting a major advisor for the Research Project, the student is required to do a minimum of two rotations of 6 weeks duration with two different BPG faculty members (Rotations in BPG (BIPG 5800).  In each rotation, the student participates in an on-going research program with a faculty member in the BPG Program.

2) A Scholarly Project (BIPG 5900) or Thesis in Bioinformatics (BIPG 6990) is required with a minimum of 10 credit hours.  The student selects a major advisor from among BPG faculty members and must have an advisory committee composed of at least 3 members; the major advisor, plus a minimum of two others, one of whom should be a BPG faculty member.

3) The student must submit a Project Proposal for review and approval by the advisory committee prior to beginning work on the project.

 
Please click on the following link to view UT faculty members who are associated with the BPG Program, and are approved Mentors for our students.  MENTORS for BPG Students (full PDF format)

 
REQUIRED FORMS for Graduate Students: (click form name to access)

1)  Plan of Study for the Master's Degree form is required to be submitted BEFORE the student completes 12 credit hours (during the Fall 1 term).

2)  G.R.A.D. Form (Graduate Research ADvisory Committee Approval & Assurances Form) is absolutely required prior to the student beginning any research (by the end of the Fall 1 term).

3)  Thesis Forms and Additional Instructions Please review this page on the Graduate School website for specific instructions on preparing your thesis, and required forms before and after your defense. Please keep in mind that the Qualifying Exam must be taken BEFORE thesis research begins.   During the semester you are doing your thesis, you must be registered for at least one credit. This is a Graduate School requirement.  This should be a bioinformatics course.  If you wish to take a course from another program, please discuss this with your advisor and Dr. Robert Blumenthal before registering.

  
SUGGESTED COURSE OPTIONS 
Students are likely to have diverse backgrounds.  For example, some might have a background in computer science or statistics, while others may have a background in the biological sciences. The same core courses are taken by all students.  However, the electives chosen will be different.  

BUSINESS SELECTIVES
For the MSBS in BIPG, either ONE of the following College of Business & Innovation courses may be used as ONE of the elective requirements, if your thesis committee agrees.

Performance Management - HURM 6730 - This course is designed to provide practical working knowledge of the processes of setting expectations, monitoring performance, coaching and developing employees, and assessing and rewarding good performance in rapidly changing organizations

Leading with Power and Influence - MGMT 6160 - The primary focus of this course is the effective use of political and social influence in organizations. This course will develop the ability to recognize, analyze, and apply sources of power and influence beyond formal authority.

MOLECULAR SELECTIVES
BMSP631        Systems Pathophysiology I                   4cr    (Spring)

BMSP632        Systems Pathophysiology II                  4 cr   (Spring)

PUBH613        Molecular Epidemiology                         3cr    (Spring)

BIOL 5660      BGSU  GENOMICS  - Graduate Students  (Fall)      
A contemporary analysis of the molecular biological and bioinformatic methods for the study of complete genomes of organisms. Instructor: Zhaohui Xu, PhD. 

BIOL 4660      BGSU  GENOMICS - Undergraduate (Fall)  
This course provides a contemporary analysis of the complete genomes of organisms. Cutting-edge bioinformatics tools and comprehensive databases will be utilized to study the genetics, biochemistry, and evolution of organisms at genome-wide scales. This course integrates hands-on research opportunities with lectures and is suitable for majors in Biology, Microbiology, and Biochemistry. Three one-hour lectures.  Prerequisite: either BIOL 3130, BIOL 3500, or CHEM 3080.  Instructor: Zhaohui Xu, PhD

PROGRAMMING SELECTIVES
The Advanced Programming Selective will be selected from the following courses offered by various departments at UT and BGSU.  The course selected will depend on availability, scheduling and student background, with approval of the student's advisor and Thesis Committee.  Note that tuition for courses designated as undergraduate courses will have to be paid for by the student.

BGSU Dept of Computer Science (BGSU) CS 215. ADVANCED PROGRAMMING CONCEPTS II (3) Fall, Spring, Summer. Advanced programming in C++. Introduction to object oriented programming techniques. Elementary data structures including lists, stacks, and queues. Dynamic storage allocation concepts. Interactive debugging techniques and use of recursion. Prerequisite: Grade of C or better in CS 205.

 BGSU CS 500. COMPUTING FOR GRADUATE STUDENTS (3). Spring, Summer. Problem solving and computer programming techniques. Variables, loops, and other control structures, arrays, subprograms, and parameter passing. Credit not applicable toward a degree in computer science. Graded S/U.

UT Dept. of Engineering Technology CSET 4100 CGI PROGRAMMING WITH PERL AND JAVA (3 hrs) Covers Common Gateway Interface (CGI) programming on the Internet using the most popular scripting languages.  Topics include client-side progrmas, server-side programs, distributed database creation and searching.  Pre-requisite: Junior standing.

UT Department of Business Technology CMPT 2110 ADVANCED CONCEPTS IN PROGRAMMING  [4 hours] The course covers advanced programming techniques and the concepts of object‑oriented programming using a currently popular programming language (such as C++). Prerequisite: CMPT 2030 CMPT 2210 DATABASE DESIGN

UT Department of Electrical Engineering and Computer Science EECS 4/5750 MACHINE LEARNING  This course emphasizes learning algorithms and theory including concept, decision tree, neural network, computational, Bayesian, evolutionary, and reinforcement learning.

UT Department of Information Systems, Marketing, E-Commerce & Sales INFS 3160-001 OBJECT-ORIENTED PROGRAMMING MW 2:00-3:15pm ST-4050 Kunnathur, Anand (Spring) INFS 3160-002 TR 11:00-12:15 pm ST-120 Fang, Xiao INFS 3160-003 MW 5:45-7:00 pm ST-127 Zhang, Jennifer.  INFS 3160-001 Object-Oriented Program JAVA TR 5:45-7:00 pm ST-114 Fang X (Fall) INFS 3160-002 MW 2:00-3:15 pm ST-4050 Zhang J.  Programming language hierarchy, classes and objects, object-oriented terminology, development of business application both stand alone and networked.  Sorting and searching, creation and use of objects. A contemporary OOP language will be needed for projects.  Pre-requisite: INFS 3150.

INFS 3380-001 PROCEDURAL PROGRAMMING LANGUAGES  C++ TR 2:00-3:15 p.m. ST-2030 Hasan, Bassam INFS 3380-011  MTWR 3:20-5:00 p.m. ST-111 Hasan B (Summer)  An introduction to application program development using procedural programming languages.  Topics include the data environment and file organization types, sequential and random file processing methods. Prerequisite: INFS 3150

UT Department of Public Health and Homeland Security PUBH 607 GENETIC EPIDEMIOLOGY  Introduces genetic epidemiology methods, principles of population genetics including linkage and association studies used in assessing familial aggregation, and transmission patterns for identifying the genetic basis of common diseases. 

PUBH 611 CATEGORIAL DATA ANALYSIS  This course introduces the theory and application of methods for categorical data, with emphasis on biomedical and public health applications.  Topics include contingency tables, log-linear, logistic regression and Raush models, multivariate methods for matched pairs and longitudinal data.  The methods are illustrated with SAS and/or SPSS, R.

PUBH 613  MOLECULAR EPIDEMIOLOGY  This course focuses on the application of epidemiological techniques to the study of effects of occupational and environmental exposures.

 
DATA BASE MANAGEMENT SELECTIVES
The Database Management Selective will be selected from the following courses offered by various departments at UT and BGSU.  The course selected will depend on availability, scheduling and student background, with approval of the student's advisor and Thesis Committee.  Note that tuition for courses designated as undergraduate courses will have to be paid for by the student.

BGSU Dept. of Computer Science (BGSU) CS 562. DATABASE MANAGEMENT SYSTEMS (3). Fall. Semantic models for conceptual and logical design of databases. Detailed study of relational systems: design, dependency, and normal forms. Use of interactive and embedded query languages. Overview of topics such as database connectivity, security, and object-oriented systems. Prerequisites: Admission to MS in CS program, or consent of department, plus CS 202 or equivalent.

UT Department of Electrical Engineering and Computer (UT) EECS 5560 DATABASE SYSTEMS I  [3 hours] The following topics are covered: relational database modeling, query languages, design issues and implementation issued of databases. An appropriate database language is introduced and used to demonstrate principles. Prerequisite: EECS 1510

(UT) EECS 5570 DATABASE SYSTEMS II  [3 hours] The emphasis of this course is on database recovery techniques, integrity constraints and concurrency control. The similarities and differences between distributed, networked, client/server and object oriented database systems are also investigated. Prerequisite: EECS 5560

UT Department of Information Systems, Marketing, E-Commerce & Sales (UT) INFS 4620 INFORMATION STORAGE, RETRIEVAL AND DATA STRUCTURES [3 hours] Information structures and their implementation are studied. Data and file design methodologies to assist in information systems development is emphasized. Data structure implementation on contemporary computing platforms is covered. Prerequisite: INFS 3150

UT Department of Business Technology (UT) CMPT 1420 DATABASE MANAGEMENT SYSTEMS APPLICATIONS [2 hours] An analysis of the use of a DBMS in solving business problems with an emphasis on the entering, updating, manipulating, storing and retrieving of information. Prerequisite: CMPT 1100 or 1020

(UT) CMPT 2210 DATABASE DESIGN  [3 hours] Focused study of data structures and database management systems. Topics will include data modeling and data design methodologies. Prerequisite: CMPT 1020 or CMPT 1100

ELECTIVES FALL     

    BMSP633       CURRENT PROBLEMS & RESEARCH APPROACHES IN PROTEIN STRUCTURE, 2.5cr
                                  Dr. Nikolai Modyanov

    BMSP638       METHODS IN BIOMEDICAL SCIENCES, 3cr, Dr. Cynthia Smas

    BIPG689        INDEPENDENT STUDY IN BPG,1-12cr, (BPG faculty)

    PUBH613       MOLECULAR EPIDEMIOLOGY, 3cr

                         MOLECULAR EVOLUTION  - New/resurrected course by (BGSU/Dr. Scott Rogers)

    PUBH818       CANCER EPIDEMIOLOGY, 3cr, Dr. Brian Fink


ELECTIVES SPRING

      BIPG689         INDEPENDENT STUDY IN BPG, 1-12cr, (BPG faculty)

ELECTIVES SUMMER

      CHEM694        BIOINFORMATICS & MOLECULAR MODELING, 2cr,  (BGSU/Dr. Neocles Leontis)  
                                  Taught on last two weekends in June (Fri. 2-10, Sat. 10-6, Sun. 8-noon)

    CHEM694        WORKSHOP ON CURRENT TOPCS IN CHEMISTRY (1-4) 
                                   On demand.  Workshop on current topics and issues within discipline;
                                   topics vary from semester to semester.

                           BIOINFORMATICS. Every even summer mainly for math/stats students. (BGSU/Dr.Gabor Szekely)

                                                         
STUDENT LEARNING OBJECTIVES (SLO's) FOR BIOINFORMATICS MSBS DEGREE:             

Graduating students WILL BE ABLE TO:

1)     Describe mammalian and nonmammalian genome structure and function, including (for example): 

1. Coding/non-coding sequence distribution
2. Isochore structure
3. Repeated element distribution
4. Intron/exon structure and distribution
5. Distribution and dynamics of methylation
6. Transcription factor binding sites (for long- and short-range factors)

2)    Discuss the processes of genome evolution, including (for example): 

1. Mechanisms of mutation
2. Consequences and exploitation of SNPs
3. Fixation of mutations
4. Genetic drift
5. Phylogenetics
6. Major theories for the origin of novel genes
7. Nature and basis of codon bias

3)    Describe and use analytic tools associated with systems/bioinformatic approaches, including (for example): 

1. Transcriptomics – microarray analysis vs. deep sequencing
2. Proteomic mass spectroscopic methods (identification and abundance)
3. Determining statistical significance in large bioinformatic datasets
4. Determination and structure of interaction networks
5. Functional network maps 

4)    Carry out appropriate statistical analysis of sequence information, including (for example): 

1. Probabilistic methods
2. Deterministic methods
3. Machine learning methods, including Support Vector Machines (SVMs)
4. Cluster analysis

5)    Demonstrate competent use of existing bioinformatic and statistical software, including (for example): 

1. R statistical tools
2. Alignments and their interpretation
3. Phylogenetic analyses
4. Programs to predict genes and transcription factor binding sites
5. Programs to display, predict and analyze 3D biomolecule structures

6)    Develop and use basic PERL programs for bioinformatic analyses, including (for example): 

1. Familiarity with the UNIX operating system
2. Writing scripts for extracting information from databases
3. Creating databases
4. Interfacing with supercomputers

7)    Apply bioinformatic methods to clinical problems, by demonstrating understanding of: 

1. Biomarker discovery and validation
2. Major diseases such as cancer, diabetes, and autoimmunity

8)    Communicate competently both in writing and orally 

1. With fellow team members in research projects
2. With the broader scientific public

9)    Demonstrate familiarity with and adherence to research ethics.