Program in Bioinformatics & Proteomics/Genomics

                    CERTIFICATE IN BIOINFORMATICS & BIOMARKERS                  


The Bioinformatics and Biomarkers Certificate Program introduces students to the newly evolving fields of bioinformatics, proteomics and genomics, and provides a core knowledge of analytical approaches used in these fields. 

  • The curriculum is designed to complement coursework and research of students enrolled in the University of Toledo Ph.D. in Biomedical Sciences Program, but also is open to other qualified students. 
  • Students can take one or two courses per term, earning the Certificate in one or two years.
  • Currently enrolled UT PhD in Biomedical Sciences or MSBS students may take individual BPG courses as electives, with permission of the instructor. To receive a Certificate in Bioformatics and Biomarkers, an online application must be submitted here:
  • The Program is a joint effort of the University of Toledo Main and Health Science Campuses, and Bowling Green State University.


Students enrolled in the Bioinformatics and Biomarkers Certificate Program must take four courses covering the following subject areas:

1)  Introduction to the scope of bioinformatics, proteomics and genomics: "BIPG5100/7100 "Fundamentals of BPG"
2) Training in statistical methods used in BPG: BIPG5200/7200"Statistical Methods in Bioinformatics"
3)  Handling and manipulation of databases and introduction to computer programming skills needed to manipulate large quantities of nucleic acid  and protein sequence data: BIPG6100/7100 "Introduction to Bioinformatic Computation"
4) EITHER: BIPG6400/8400 Applications of BPG, in which faculty members using these methodologies will discuss and demonstrate how these techniques are utilized to solve research problems:
    OR: BRIM6200/8200 "Biomarker Discovery, Validation and Implementation", in which faculty provide an overview of biomedical discovery and validation techniques followed by application in selected aspects of individualized medicine.

Upon completion of the Program, students will be prepared to utilize BPG research techniques and be able to interact with specialists in each BPG subdiscipline.

The curriculum consists of four, 3-credit courses (listed below). If you are in a doctoral program, the second (higher) course number is the one for which you should register.

Course No.                       Course Title, Description & Credits
Fall Year 1
BIPG5100/7100                Fundamentals of Bioinformatics and Proteomics/Genomics, 3 cr

                                         Introduction to scope of bioinformatics, proteomics and genomics

BIPG5200/7200                Statistical Methods in Bioinformatics, 3 cr
                                         Training in statistical methods used in BPG

Spring Year 1
BIPG6100/8100                Introduction to Bioinformatic Computation, 3 cr
                                         Handling and manipulation of databases and introduction to computer programming skills
                                         needed to manipulate large quantities of nucleic acid and protein sequence data.

EITHER:  BIPG6400/8400              Application of Bioinformatics and Proteomics/Genomics, 3 cr
                                                    Faculty members using these methodologies will discuss and demonstrate how these techniques
                                                    are utilized to solve research problems.    

OR:        BRIM6200/8200             Biomarker Discovery, Validation & Implementation, 3cr
                                                    Faculty provide an overview of biomedical discovery and validation techniques
                                                    followed by application in selected aspects of individualized medicine.

*BMSP6340 Current Problems & Research Approaches in Genes and Genomes, or equivalent course approved by the BPG Program, is required for admission into the BPG Certificate Program.


Applicants who are University of Toledo students must submit the following after applying online (application link below)

1) Official transcripts
2) Statement of purpose
3) One letter of recommendation is required. It must be signed, and on official letterhead. Two additional letters are optional, HOWEVER, in the event that a student decides to pursue the BPG MSBS degree, it will save time to have the required total of three letters of recommendation already on file.

Applicants who are NOT presently enrolled in classes at The University of Toledo must follow the requirements below, and submit the following through the online application (application link below):

1) Earned baccalaureate and GRE, or earned graduate degree from an accredited college or university
2) Minimum 3.0 undergraduate GPA; degree in process will be considered.
3) Minimum GRE 300 or minimum requirements set for the UT Ph.D. in Biomedical Sciences or MSBS programs
4) Official transcripts
5) Three (3) letters of recommendation, signed, and on official letterhead
6) Completed electronic application and $45.00 application fee

All applications will be reviewed by the BPG/BRIM Program Admissions Committee.

To receive a Certificate in Bioinformatics and Biomarkers, application must be submitted online at the following link:

Electronic, online application must be filed ONLY for those seeking a Certificate.  If a student takes all four courses, and does not formally apply online, they will NOT receive a Certificate.

After being accepted into the Certificate Program, the following form is required to be submitted to the College of Graduate Studies:

PLAN OF STUDY:  A partially-completed Plan of Study for the Certificate can be found here.  Please complete the top portion and obtain the required signatures on Page 2.


Students completing the Certificate Program 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 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)    Understand 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)    Describe 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 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)    Describe application of bioinformatic methods to clinical problems, by demonstrating understanding of:

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


Last Updated: 11/25/15