Biostatistics/Bioinformatics is an important research field in Statistics with immensely broad applications in public health, medical, and biological research. Bioinformatics is an emerging field with rapid development and has significant overlap with Biostatistics. The Bioinformatics/Biostatistics (STAT-BB) concentration addresses the increasing research opportunities and the educational needs of this burgeoning field.

**Description**

The STAT-BB Concentration offers Master's and Ph.D. degrees for graduate study and research concentrations in Biostatistics and Bioinformatics. The Concentration is administered by the Statistics (STAT) Program within the Mathematics Department. Its faculty includes professors in the STAT Program, in the Department of Epidemiology and Biostatistics (EPIB) and in the Center for Bioinformatics and Computational Biology (CBCB) at UMCP. The program also includes participation of Division of Biostatistics and Bioinformatics (DBB) faculty at the University of Maryland School of Medicine (SOM). STAT faculty and EPIB faculty collaborate on program admissions decisions, academic policies and creating qualifying exams.

Students may select with advisement an appropriate sequence of courses and a research area to form an individual plan of study under the guidance of a faculty member from STAT, EPIB, or CBCB at UMCP or from the DBB/SOM at UMB. The program has the flexibility to accommodate student’s individual background and interests, and offers the opportunity to select courses to supplement the core coursework. Students in this program have opportunities to work on research projects directly with the faculty from the participating programs.

STAT-BB is administratively affiliated with the Department of Mathematics, which maintains the records of all students in the STAT-BB Concentration and handles correspondence with those applying for admission. Applicants for admission must indicate that the student wishes to enter the STAT-BB Concentration and the appropriate specialization, e.g., STAT-BB with (sub-) specialization STAT or (sub-) specialization EPIB. All participating faculty will be listed in all materials describing the STAT-BB program.

An Advisory Committee, consisting of STAT and EPIB faculty, with a representative from DBB, will advise the Statistics Program Director on all matters of program policies and operational decisions. STAT and EPIB faculty will also comprise an Admissions Committee and will collaborate on administering qualifying exams. The EPIB specialization will have a designated lead faculty member who will coordinate for the EPIB faculty. Students admitted to a (sub) specialization will normally matriculate in that (sub) specialization, and all student selections of advisor will require the approval of the Advisory Committee and the Statistics Program Director. Faculty from the participating programs will be eligible to advise dissertations and theses.

#### How to Apply - University of Maryland's Graduate Application Process

Applicants interested in the Biostatistics/Bioinformatics concentration **must apply to the STAT Program** through the University of Maryland's on-line application system, described below. Be sure to indicate your interest in STAT-BB. **Do not apply through SOPHAS.**

The University of Maryland's Graduate School accepts applications through its ApplyYourself/Hobsons application system.**Before completing the application, applicants are asked to check the Admissions Requirements site for specific instructions and additional requirements (select your program of interest).**

As required by the Graduate School, all application materials are to be submitted electronically:

- Graduate application
- Transcripts
- Statement of purpose
- Letters of recommendation (3)
- Graduate Record Examination (GRE)
- TOEFL/IELTS (International students only - required even if eligible for waiver)
- Program/Department supporting documents (as applicable)
- Non-refundable application fee ($75) for each program to which an applicant applies
- Please check the
**Admissions Requirements**site for additional requirements

The electronic submission of application materials helps expedite the review of an application. Completed applications are reviewed by an admissions committee in each graduate degree program. The recommendations of the committees are submitted to the Dean of the Graduate School, who will make the final admission decision. Students seeking to complete graduate work at the University of Maryland for degree puposes must be formally admitted to the Graduate School by the Dean. To ensure the integrity of the application process, the University of Maryland authenticates submitted materials through TurnItIn for Admissions.

**Master of Arts (M.A.) Degree Requirements: **

The M.A. degree program requires a student to complete 30 credit hours with at least a B average (3.0 on a 4.0 scale); at least 18 of these credits must be at the graduate level (600/700 level), and at least 12 of the graduate credits must be in Statistics (STAT). Students must complete a Scholarly paper and satisfy the STAT-BB Master's qualifying requirements (see below). The following courses are required:

- STAT 410: Introduction to Probability Theory
- STAT 650: Applied Stochastic Processes
- STAT 700: Mathematical Statistics I
- STAT 701: Mathematical Statistics II
- STAT 705: Computational Statistics
- STAT 702: Survival Analysis (or EPIB 653 Survival Data Analysis)

Students interested in bioinformatics will complete the required coursework and can select specialized courses, such as CMSC 423 Bioinformatic Algorithms, Databases and Tools; CMSC 701 Computational Genomics, and CMSC 702 Computational Systems Biology. Interested students can then work on their scholarly paper with a faculty mentor with expertise in computational biology. Interested students will be expected to have a solid background in computer science for this option.

It is anticipated that STAT 702 (which focuses on the general theory of survival analysis) will be offered in the Fall semester, while EPIB 653 (which focuses on applied survival data analysis) will be offered in the Spring semester. In addition, each student is required to take at least three graduate level courses in STAT, EPIB or CMSC with the approval of the (Advisory Committee). Part-time M.A. students may require a longer time to complete the STAT-BB program, but not longer than 5 years.

**Doctor of Philosophy (Ph.D) Requirements: **

A Master’s degree is not required for admission to the Ph.D. program. A doctoral student must complete a minimum of 36 hours of formal courses (at least 27 at the 600/700 level) with at least a B average (3.0 on a 4.0 scale); at least 18 of the graduate credits must be taken in Statistics. In addition, the University requires at least 12 hours of STAT 899 or EPIB 899 (Doctoral research) given by any participating faculty member as the major advisor.

Ph.D. students must satisfy the Ph.D. qualifying requirements (see below). Full-time students must satisfy all qualifying requirements by the middle of the third year. Part-time students must satisfy all qualifying requirements by the end of the fourth year. If successful in the written examinations, the student must pass an oral exam. Administered by the faculty under this proposed joint program, the oral exam usually takes place a year after the student passes the written examination. This exam serves as a test of the student's in-depth preparation in the area of specialization and research potential. Successful completion of the oral exam indicates that the student is ready to begin writing the doctoral dissertation. In addition, the Department requires a reading competence in one foreign language for the Ph.D. To be admitted to candidacy, the Ph.D. student must pass the written examinations and the oral examination. The final step in completion of the doctoral study for a student is to pass the final oral exam on the dissertation.

The following courses are required:

- STAT 410 Introduction to Probability Theory
- STAT 650 Applied Stochastic Processes
- STAT 700 Mathematical Statistics I
- STAT 701 Mathematical Statistics II
- STAT 705 Computational Statistics
- STAT 740 Linear Statistical Models I
- STAT 741 Linear Statistical Models II (STAT 740 is the prerequisite)
- STAT 770 Analysis of Categorical Data
- STAT 702 Survival Analysis
- STAT 899 or EPIB 899 Doctoral Research (12 credits)

Each student is required to take at least three additional courses in STAT, EPIB or CMSC )with the approval of the Advisory Committee).. For students who focus their studies on Biostatistics, it is required to take at least two of the following three courses:

- EPIB 652 Categorical Data Analysis
- EPIB 653 Applied Survival Data Analysis
- EPIB 655 Longitudinal Data Analysis

Students interested in bioinformatics will complete the required coursework and can select specialized courses such as CMSC 423 Bioinformatic Algorithms, Databases and Tools; CMSC 701 Computational Genomics or CMSC 702 Computational Systems Biology. Interested students can then select a faculty advisor with expertise in computational biology. Interested students will be expected to have a solid background in computer science for this option.

#### Qualifying Requirements for Ph.D. students:

1. Students must pass at least two written qualifying exams at the Ph.D. level from the following list:

- Statistics (based on STAT 700-701)
- Applied Statistics (based on STAT 740-741)
- Applied Probability (based on STAT 410-650)
- Biostatistics/Bioinformatics

These examinations will take place twice a year in January and August at the same time as the usual qualifying exams of the STAT program. The problems required for STAT-BB students in these exams will come from and be graded by the relevant faculty members who have taught those courses. A student may take one or more examinations at a time.

2. Students who choose to take only two written qualifying exams must take four semesters of coursework from the list below:

- STAT 650* (Applied Stochastic Processes)
- STAT 700, STAT 701* (Mathematical Statistics I, II)
- STAT 740, STAT 741* (Applied Statistics I, II)
- STAT 702 (Survival Analysis)
- STAT 705 (Computational Statistics)
- STAT 770 (Categorical Data Analysis)
- EPIB 652 (Applied Categorical Analysis)
- EPIB 653 (Applied Survival Analysis)
- EPIB 655 (Longitudinal Data Analysis)
- CMSC 701 (Computational Genomics)
- CMSC 702 (Computational Systems Biology)

The grade in each of the four courses must be B (3.0) or better, and students must attain a GPA of at least 3.3 for the courses used to satisfy this requirement. Each of the courses used to satisfy this requirement must have serious assessments (graded homeworks, projects, etc.) There should be an assessment which can only be completed by the student, ( for example, in-class exams or oral presentations but not homework).

3. Courses marked with * may not be used to satisfy this requirement if the student has taken the corresponding written qualifying exam. For example, a student who passes the Applied Statistics exam may not use STAT 741 to satisfy Requirement 2.

#### Qualifying Requirements for Master's students:

1. Students must pass at least two written qualifying exams at the Master's level from the following list:

- Statistics (based on STAT 700-701)
- Applied Statistics (based on STAT 740-741)
- Applied Probability (based on STAT 410-650)
- Biostatistics/Bioinformatics

These examinations will take place twice a year in January and August at the same time as the usual qualifying exams of the STAT program. The problems required for STAT-BB students in these exams will come from and be graded by the relevant faculty members who have taught those courses. A student may take one or more examinations at a time.

2. Students who choose to take only two written qualifying exams must take three semesters of coursework from the list below:

- STAT 650* (Applied Stochastic Processes)
- STAT 700, STAT 701* (Mathematical Statistics I, II)
- STAT 740, STAT 741* (Applied Statistics I, II)
- STAT 702 (Survival Analysis)
- STAT 705 (Computational Statistics)
- STAT 770 (Categorical Data Analysis)
- EPIB 652 (Applied Categorical Analysis)
- EPIB 653 (Applied Survival Analysis)
- EPIB 655 (Longitudinal Data Analysis)
- CMSC 701 (Computational Genomics)
- CMSC 702 (Computational Systems Biology)

The grade in each of the three courses must be B (3.0) or better, and students must attain a GPA of at least 3.3 for the courses used to satisfy this requirement. Each of the courses used to satisfy this requirement must have serious assessments (graded homeworks, projects, etc.) There should be an assessment which can only be completed by the student, ( for example, in-class exams or oral presentations but not homework).

3. Courses marked with * may not be used to satisfy this requirement if the student has taken the corresponding written qualifying exam. For example, a student who passes the Applied Statistics exam may not use STAT 741 to satisfy Requirement 2.

**Policies on Dissertation Advisors and Candidacy Exams:**

- Before taking the candidacy exam, each student must officially declare his/her dissertation advisor(s) by informing the Statistics Program Director. Each student will have an internal (co)advisor from either STAT or EPIB and may also have an external participating faculty member as (co)advisor. The STAT or EPIB (co)advisor will chair the dissertation committee. The Advisory Committee will advise the Statistics Program Director on the suitability of faculty as participating advisors.
- Due to the vast breadth of this STAT-BB program, if a student passes the oral candidacy exam under one advisor and later wishes to change to a different dissertation advisor, upon the advice and decision of the Advisory Committee and Statistics Program Director, it may be required that the student first study under the new advisor, then re-take the candidacy exam.

The participating faculty will include members of the STAT and EPIB programs and certain members of the Computer Science Department (those specializing in bioinformatics). There will also be an association with faculty members of the Medical School at the U-M Baltimore campus.