UCLA Bioinformatics PhD Program Requirements: A Comprehensive Guide

The Bioinformatics Interdepartmental Ph.D. Program at UCLA is a multidisciplinary program within the Graduate Programs in Bioscience (GPB). It fosters a shared interest in research areas and approaches among faculty and students. This guide outlines the requirements for the Ph.D. program, covering coursework, examinations, research, and other essential components.

Program Overview

The Bioinformatics Interdepartmental Ph.D. Program is one of ten disciplinary “Home Areas” within the University of California, Los Angeles (UCLA) Graduate Programs in Bioscience (GPB). Home Areas consist of faculty and students with shared interest in research areas and approaches. Bioinformatics is an interdepartmental program and the major for the following home areas in Graduate Programs in Bioscience: Bioinformatics, Medical Informatics, and Systems Biology. The program encourages applications from students in all areas of science, with successful applicants expected to have or acquire a background comparable to the requirements for UCLA's bachelor's degree in Computational and Systems Biology. A background in computer science and mathematics is desirable. Applicants with deficiencies in these or other subjects should address these deficiencies at the earliest opportunity, generally by preparatory study at an appropriate institution.

Academic Advising and Guidance

All academic affairs for graduate students in the program are directed by the program’s faculty graduate adviser, who is assisted by staff in the Graduate Student Affairs Office. The chair of the guidance committee acts as the provisional adviser until a permanent adviser is selected. Provisional advisers are not committed to supervise examination or thesis work and students are not committed to the provisional adviser.

Master's Degree Requirements (Field 1: Bioinformatics)

Students in Field 1 (Bioinformatics) must be enrolled full time and complete 36 units (nine courses) of graduate (200 or 500 series) or upper division (100 series) course work for the master’s degree. Within this overall requirement, students must complete 20 units (five courses) at the graduate level for a letter grade. Students must complete all of the following:

Bioinformatics M229S: Current Topics in Bioinformatics
Bioinformatics M223: Statistical Methods in Bioinformatics
Bioinformatics M275A and B: Applied Bioinformatics
Two electives from the Program’s list of approved elective courses. These two electives require the approval of the student’s PI/faculty mentor. Please note: other elective courses outside of the Program’s list can be taken with the agreement of the Home Area Director and the student’s PI/faculty mentor.
Enrollment in Bioinformatics 201 is expected throughout study for the master’s degree.
Enrollment in Bioinformatics 596 research units, although no more than two courses (eight units) of 596 may be applied toward the requirements for a master’s degree.

Master's Capstone Project

The master’s capstone is an individual project in the format of a written report resulting from a research project. The report should describe the results of the student’s investigation of a problem in the area of bioinformatics under the supervision of a faculty member in the program, who approves the subject and plan of the project, as well as reading and approving the completed report. While the problem may be one of only limited scope, the report must exhibit a satisfactory style, organization, and depth of understanding of the subject. A student should normally start to plan the project at least one quarter before the award of the M.S. degree is expected. The advisory committee evaluates and grades the written report as not pass or M.S. The capstone plan is available for students pursuing the Bioinformatics field and the Medical Informatics field.

Thesis Proposal and Evaluation

Students must choose a permanent faculty adviser and submit a thesis proposal by the end of the third quarter of study. The proposal must be approved by the permanent adviser who served as the thesis adviser. The thesis is evaluated by a three-person committee that is nominated by the program and appointed by the Division of Graduate Education.

Doctoral Program Requirements

Mentor Selection

Upon entering their second year in the Bioinformatics IDP Program, students will select a mentor who will serve as their dissertation chair, research advisor, and primary graduate advisor.

Coursework

Doctoral students must complete specific core courses depending on their chosen field.

Bioinformatics: Students must complete all of the following: (1) Bioinformatics M229S: Current Topics in Bioinformatics; (2) Bioinformatics M223: Statistical Methods in Bioinformatics; (3) Bioinformatics M275A and B: Applied Bioinformatics; (4) one of the Data Science course chosen from the Program’s list of approved elective courses; This course requires the approval of the student’s PI/faculty mentor; (5) two additional Data Science or other elective courses chosen from the Program’s approved list elective courses shall be completed before the oral qualifying exam. These two elective courses require the approval of the student’s PI/faculty mentor. Please note: other elective courses can be taken with the agreement of the Home Area Director and the student’s PI/faculty mentor; (6) MIMG C234; (7) enrollment in Bioinformatics 201 is expected throughout the first two years; (8) Bioinformatics 202 in the Fall of the first year and the Spring of the first and second years; (9) three laboratory rotations (enrolling in six units of Bioinformatics 596 during each rotation); and (10) Bioinformatics 596 or 599 in each quarter after the first year.
Medical Informatics: Students must complete all of the following: (1) nine core courses (34 units) Bioengineering 220, 223A, 223B, 223C, 224A, 224B, M226, M227, and M228; (2) MIMG C234; (3) 8 units of Bioinformatics 596; (4) 4 units of 200-level seminar or journal club courses approved by the program; and (5) six electives, chosen from the following list: Bioinformatics M223, M226; Biomathematics 210, M230, M281, M282; Biostatistics 213, M232, M234, M235, 241, 276; Computer Science 240A, 240B, 241B, 245, 246, 247, 262A, M262C, 262Z, 263A, 265A, M268, M276A; Electrical and Computer Engineering 206, 210A, 210B, 211A, M217, 219; Information Studies 228, 246, 272, 277; Linguistics 218, 232; Neuroscience CM272; Physics in Biology and Medicine 210, 214. M248; Statistics 221, M231A, M231B, M232A, M232B, 238, M241, M243, M250, 256.
Systems Biology: Students must complete all of the following: (1) eight core courses (30 units) Bioengineering 220, 223A, 223B, one course from BE 224A or Bioinformatics M223 or M226, BE 224B, BE M226, BE M227, and BE M228; (2) MIMG C234; (3) eight units of Bioinformatics 596; (4) four units of 200-level seminar or journal club courses approved by the program; and (5) six electives, chosen from the following list: Bioinformatics M223, M226; Biomathematics 210, M230, M281, M282; Biostatistics 213, M232, M234, M235, 241, 276; Computer Science 240A, 240B, 241B, 245, 246, 247, 262A, M262C, 262Z, 263A, 265A, M268, M276A; Electrical and Computer Engineering 206, 210A, 210B, 211A, M217, 219; Information Studies 228, 246, 272, 277; Linguistics 218, 232; Neuroscience CM272; Physics in Biology and Medicine 210, 214. M248; Statistics 221, M231A, M231B, M232A, M232B, 238, M241, M243, M250, 256.

Please note: other elective courses can be taken with the agreement of the Home Area Director and the student’s PI/faculty mentor.

Full-Time Enrollment

Students are required to enroll full-time in a minimum of 12 units each quarter.

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Addressing Gaps in Training

Students who have gaps in their previous training may take, with their thesis adviser’s approval, appropriate undergraduate courses. For example, students without statistical background are recommended to take STATS 100B (Introduction to Mathematics Statistics) in their 1st year. Students without a Computer Science background are recommended to take COM SCI 180 (Introduction to Algorithms and Complexity), COM SCI 145 (Introduction to Data Mining), COM SCI 146 (Introduction to Machine Learning), or COM SCI 148 (Introduction to Data Science).

Teaching Experience

One quarter of teaching experience is required by the end of the third year.

Qualifying Examinations

Academic Senate regulations require all doctoral students to complete and pass university written and oral qualifying examinations prior to doctoral advancement to candidacy. Also, under Senate regulations, the University Oral Qualifying Examination is open only to the student and appointed members of the doctoral committee. In addition to university requirements, some graduate programs have other pre-candidacy examination requirements. Doctoral students must complete the core courses described above before they are permitted to take the written and oral qualifying examinations. Students are required to pass a written qualifying examination that consists of a research proposal outside of their dissertation topic and the University Oral Qualifying Examination in which they defend their dissertation research proposal before their doctoral committee. Students are expected to complete the written examination in the summer following the first year and the oral qualifying examination by the end of fall quarter of the third year. During their first year, doctoral students perform laboratory rotations with program faculty whose research is of interest to them and select a dissertation adviser from the program faculty inside list by the end of their third quarter of enrollment.

Written Qualifying Examination (WQE)

The Written Qualifying Examination (WQE) must take place in the summer following the first year of doctoral study. In order to be eligible to take the WQE, students must have achieved at least two passing lab rotation evaluations, as well as at least a B average in all course work. Students are expected to formulate a testable research question and answer it, by carrying out a small, well-defined and focused project over a fixed one-month period. It must include the development of novel bioinformatic methodology. The topic and methodologies are to be selected by the student. The topic requires advance approval by the faculty committee, and may not be a project from a previous course, a rotation project, a project related to the student’s prior research experience, an anticipated dissertation research topic, or an active or anticipated research project in the laboratory of the student’s mentor. The WQE must be the student’s own ideas and work exclusively. Students are expected to complete a WQE paper of publication quality (except for originality), with a maximum length of 10 pages, single-spaced, excluding figures and references. This paper is submitted to the Student Affairs Office and graded by a faculty committee on a pass or no-pass basis.

University Oral Qualifying Examination

The University Oral Qualifying Examination must be completed and passed by the end of the fall quarter of the third year. Students prepare a written description of the scientific background of their proposed dissertation research project, the specific aims of the project, preliminary findings, and proposed bioinformatic approaches for addressing the specific aims. This dissertation proposal must be written following an NIH research grant application format and be at least six pages, single spaced and excluding references, and is submitted to the students’ doctoral committee at least 10 days in advance of the examination. Exclusive of their doctoral committee members, students are free to consult with their dissertation adviser, or other individuals in formulating the proposed research. The examination consists of an oral presentation of the proposal by the student to the committee. The student’s oral presentation and examination are expected to demonstrate: (1) a scholarly understanding of the background of the research proposal; (2) well-designed and testable aims; (3) a critical understanding of the bioinformatic, mathematical or statistical methodologies to be employed in the proposed research; and (4) an understanding of potential bioinformatic outcomes and their interpretation. This examination is graded Pass, Conditional Pass, or Fail. If the doctoral committee decides that the examination reflects performance below the expected mastery of graduate-level content, the committee may vote to give the student a Conditional Pass. A student who receives a Conditional Pass will be required to modify or re-write their research proposal, so as to bring it up to required standard. In the case of a Conditional Pass, the student will be permitted to seek the advice of their committee in modifying or re-writing the proposal. Any required re-write or modification will be submitted to, and reviewed by the doctoral committee. A second oral presentation is not necessary unless the doctoral committee requires so. The signed Report on the Oral Qualifying Examination & Request for Advancement to Candidacy will be retained in the Graduate Student Affairs Office until the student has satisfied the doctoral committee’s request for revision or re-write. Students are expected to complete the written qualifying examination in the summer following the first year of study and the University Oral Qualifying Examination by the end of fall quarter of the third year.

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Annual Requirements

Annual Committee Meetings: Beginning one year after advancement to doctoral candidacy, and in each year thereafter until completion of the degree program, students are required to meet annually with their doctoral committee. At each meeting, students give a brief, 30-minute oral presentation of their dissertation research progress to their committee. The purpose of the meeting is to monitor the student’s progress, identify difficulties that may occur as the student progresses toward successful completion of the dissertation and, if necessary, approve changes in the dissertation project.
Annual Progress Report: All students are required to submit a brief report (a one-page form is provided) of their time-to-degree progress and research activities indicating the principal research undertaken and any important results, research plans for the next year, conferences attended, seminars given, and publications appearing or manuscripts in preparation.

Academic Disqualification

A student who fails to meet the above requirements may be recommended for academic disqualification from graduate study. A graduate student may be disqualified from continuing in the graduate program for a variety of reasons. The most common is failure to maintain the minimum cumulative grade point average (3.00) required by the Academic Senate to remain in good standing (some programs require a higher grade point average). Other examples include failure of examinations, lack of timely progress toward the degree and poor performance in core courses. Probationary students (those with cumulative grade point averages below 3.00) are subject to immediate dismissal upon the recommendation of their department. Students must receive at least a grade of B- in core courses or repeat the course. Students who received three grades of B- or lower in core courses, who fail all or part of the written or oral qualifying examinations twice, or who fail to maintain minimum progress may be recommended for academic disqualification by vote of the entire interdepartmental program committee. Failure to identify and maintain a thesis adviser is a basis for recommendation for academic disqualification.

Tuition and Fees

The tuition fee is 33238 USD / year.

Campus Location

The campus location is Beverly Hills, United States.

Additional Information

This field of study provides exposure primarily to biological and algorithmic advances in genomics, proteomics, and other related fields. Study consists of a core curriculum, computer science, mathematics, and statistics. This field of study exposes students to foundational concepts in medical informatics, providing a background in clinical data, big data management, and analyses of new and emergent data utilized to guide biomedical research and healthcare.

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