UCLA Bioinformatics: The Philosophy of the Ph.D. Program

UCLA | Bioinformatics

(This post is a collaboration between the instructors of the core courses for the UCLA Bioinformatics programs: Eleazar Eskin, Chris Lee, Wei Wang, Bogdan Pasaniuc, Jason Ernst, Sriram Sankararaman, and Jessica Li, along with the current director of the program, Yi Xing.)

Bioinformatics is an interdisciplinary field that combines different aspects of quantitative sciences, such as Computer Science, Statistics, and Mathematics, with biological sciences, such as Molecular Biology and Genetics.  Training programs in quantitative sciences and biomedical sciences have very different cultures and structures, particularly at the doctoral level.  At UCLA, we aim to combine the best of both worlds with the Interdepartmental Bioinformatics Ph.D. program.

We established our Ph.D. program in 2008, and we enroll 6 to 10 Ph.D. students each year. Over 45 faculty specializing in computational and experimental biology are associated with the Bioinformatics Ph.D. program, with active research and education programs spanning biology, mathematics, engineering, and medicine. The program encompasses the breadth of the growing Bioinformatics field by offering courses from over 12 departments.  The Bioinformatics Ph.D. is not housed in any one department but is an Interdepartmental Program (IDP) whose faculty are members of 17 UCLA departments.  The IDP is an administrative unit designed for multidisciplinary academic programs.   This unit also administers the Biomedical Informatics Ph.D. program and will administer the planned Ph.D. program in Systems Biology.

For many aspects of the UCLA Bioinformatics Ph.D. program, we draw upon different ideas from the cultures of Quantitative and Biomedical training programs.

In traditional Biomedical science Ph.D. programs, the majority of a student’s training in applied sciences takes place through mentorship in the laboratory.  Students do take some courses during their first year, but these courses mainly cover recent research in the field and are often team-taught by multiple faculty.  These courses typically require only minimal work outside of class.  During the first year of the Ph.D. program, these students focus on identifying a research lab to join by completing rotations in three labs.  Starting with their second year, students become members of their chosen lab and perform research full time.

On the other hand, in traditional quantitative science Ph.D. programs, the majority of a student’s training takes place didactically through challenging coursework.  In these programs, coursework consumes at least 50% of the student’s time during their first two years.  These intensive courses are usually taught by a single instructor (or sometimes a team of two) and require substantial homework assignments, course projects, and exams.  However, the courses lay a foundation for the technical skills that will become the basis of a student’s future research.  Students admitted to these types of programs are encouraged to join the research lab of a specific professor and start research right away.

Here we describe how we combine these two cultures with the principles and philosophy that guided the design of our Ph.D. Program.

  1. Training in Methodology Development. The UCLA Bioinformatics program is uniquely focused on preparing our students to develop novel methodologies that can contribute to important biological problems.  Students who are interested in methodology development are a great fit for our program.  Our program is able to maintain this focus, because UCLA hosts many other Ph.D. programs that can accommodate students interested in Bioinformatics but prefer a program with a different, sometimes more traditional, focus. These include the recently established Genetics and Genomics Ph.D. program, which has focuses less on methodology development and prioritizes biological discovery.

    UCLA also has a broad set of other Ph.D. programs in quantitative sciences, such as Statistics and Computer Science, which also accommodate students who are interested in Ph.D. research in Bioinformatics  but are primarily interested in a quantitative sciences training program.  UCLA also offers Ph.D.  programs in Biomathematics, Biomedical Informatics and Biostatistics for students interested in other areas of Computational Biology.  In addition, a new graduate program in Systems Biology is being developed in conjunction with the Bioinformatics IDP.  The multitude of programs at UCLA enable students to join a program with similar goals in terms of their training which in turn allows the programs to be organized around these goals.

  2. Our Core Curriculum Provides Rigorous Computational Training. Our core courses are structured in the style of a quantitative Ph.D. program, complete with rigorous training requirements that are met through homework assignments, exams, and course projects. The philosophy behind our courses is to teach fundamental concepts in computation and use Bioinformatics to explore these concepts.

    For this reason, our core courses are rigorous enough to satisfy course requirements in quantitative Ph.D. programs at UCLA, including those for the Computer Science and Statistics graduate programs.  Bioinformatics core courses are taught and administered by faculty who have appointments in these quantitative departments.  Six of the courses are administered by the Computer Science Department, and one by the Statistics Department. Our rigorous core curriculum appeals to students in these programs as well as students in the Bioinformatics Ph.D. program. In fact, the majority of students enrolled our core courses are from quantitative graduate programs. This diversity of academic disciplines brings to these courses a high level of engagement and creativity.

  3. Substantial Didactic Training in Bioinformatics. Similar to a traditional quantitative sciences training program, our program offers a full load of Bioinformatics Courses. Our program includes five core courses that we strongly recommended students take during their first year.  These courses are: Introduction to Bioinformatics (Chris Lee), Algorithms in Bioinformatics (Eleazar Eskin), Methods in Computational Genomics (Jason Ernst and Bogdan Pasaniuc), Statistical Methods in Bioinformatics (Jessica Li), and Computational Genetics (Eleazar Eskin).

    In addition, students are encouraged to take during their second year Machine Learning in Bioinformatics (Sriram Sankararaman) as well as the multiple offerings of Current Topics in Bioinformatics (rotating faculty).  The Current Topics courses cover relevant issues such as Data Mining in Bioinformatics or Advanced Computational Genetics.  We designed the coursework for the UCLA Bioinformatics Ph.D. program so that students can take many skills-building courses comparable to those offered by a traditional quantitative science program.

  4. Rotation Program. Upon entering a Ph.D. program, students typically do not yet know whose lab they want to join. For this reason, we adopt a rotation program styled after typical Biomedical training programs.  Here, students undertake three 10-week rotations; one rotation during each of the three academic quarters of their first year.  Students use a rotation to try out a lab, and decide on a lab to join by the end of their first year in graduate school. Secondary, but important goals of the Rotation Program, are to develop diverse research skills, and to develop a collaborative network that may benefit the doctoral research project and career development.

  5. Seminar Program. An important aspect of Biomedical training programs is the informal training provided during seminars and journal clubs. The UCLA Bioinformatics Ph.D. program leverages informal training with a seminar that students are required to attend for the first two years of the program.  In fact, the weekly Bioinformatics Seminar series has become a key focal point of the UCLA Bioinformatics community.  Students also organize an annual overnight retreat where they share and get feedback on their research.

  6. Research Oriented Written Qualifier. Every Ph.D. program requires completion of a written qualifying exam, which typically occurs after coursework is completed. In traditional biomedical science programs, this exam is often preparation of a grant proposal in a topic of the student’s choice.  In traditional quantitative science Ph.D. programs, this requirement is often a challenging written exam covering topics in coursework. More recently, quantitative Ph.D. programs have abandoned the written qualifier and replaced it with an exam where the students write a paper demonstrating their research skills.

    In the UCLA Bioinformatics Ph.D. program, we have adopted such an exam.  After completion of first year courses, and faculty approval of their project proposal, students are given a one-month period to work independently on the project and to submit a written research paper reporting their results. Faculty in the program review the resulting papers. Although these projects are often small in scope because of the exam’s time constraints, the resulting papers are required to exhibit: 1) high quality in writing, 2) contextualizing the project within existing research, 3) supporting conclusions with chosen experiments, and 4) logical flow of the arguments in the paper.  The idea behind the exam is not to weed out students who cannot pass it, but to set an objective bar for achievement that the students can attain.

Just as Bioinformatics is an interdisciplinary field that combines methods, data, and theories from different academic traditions, the UCLA Bioinformatics Ph.D. is earned in an interdisciplinary program that combines aspects of the training cultures of quantitative and biological sciences. Our unit is a new kind of program that has been specifically designed to administer a rigorous, cross-sectional training in methodology development.

 

UCLA Bioinformatics: The Philosophy of the Undergraduate Program

Bioinformatics is an important interdisciplinary research area with tremendous opportunities in graduate training and industry employment.  Yet, few academic institutions offer undergraduate programs designed to prepare students for opportunities in Bioinformatics.

The UCLA Undergraduate Bioinformatics Minor is an academic program established in Fall 2012 at UCLA.  Undergraduates in any Major can obtain a Bioinformatics Minor by completing an additional 8 courses. Since Fall 2012, approximately 80 students have joined the Minor program. These students represent Majors in over a dozen UCLA departments, including: Computer Science; Chemistry; Molecular, Cell, & Developmental Biology; Microbiology, Immunology, and Molecular Genetics; Ecology and Evolutionary Biology; and Computational and Systems Biology.

Over 45 faculty specializing in computational and experimental biology are associated with the Bioinformatics Minor, spanning the fields of biology, mathematics, engineering, and medicine. Course offerings from more than 12 unique departments allow the Minor program to encompass the breadth of the growing Bioinformatics field.

Here we describe the principles and philosophy that guided the design of our Minor.

  1. Our Core Bioinformatics Courses Teach Interdisciplinary Computation. The foundation of our program is the cluster of three integrated core courses in Bioinformatics. These courses are truly interdisciplinary; they satisfy elective requirements in multiple departments and recruit students from different Majors to the Minor program. These core courses build upon the philosophy that students must first learn fundamental concepts in computation in order to later explore problems in Bioinformatics.  These courses offer basic skills and appeal to many students beyond those interested in Bioinformatics.
  1. Rigorous Background in Computation. To be successful in Bioinformatics, students must have a solid background in both computation and Biology. Our core courses require as prerequisites a substantial background in computation and statistics. To enter the Minor, we require that students have completed one year of programming and one upper division Statistics course.  To complete the Minor, our students take Linear Algebra and one upper division course on Algorithms taught by the Computer Science or Math Department.  Our students also take a Molecular Biology course taught by the Life Sciences Department. We believe that it is important for faculty in Computer Science and Program in Computing to teach programming, and for faculty in the Life Sciences to teach Biology. Further, it is important for students to take the same programming classes as do their peers in Engineering majors, and for students to take the same Biology classes alongside their peers in Life Sciences.
  1. The Bioinformatics Minor Builds upon the Students’ Major. Every student graduating from UCLA with a Bioinformatics Minor also completes an academic Major program. While we do adjust the Minor curriculum to help students efficiently complete both their Major and Minor requirements within 4 years, each of our graduates has exactly the same amount of training in their Major as fellow Majors who are not in the Minor.  This avoids a common pitfall in interdisciplinary education: students only receive a superficial background in each academic area.
  1. Bioinformatics is a Research Oriented Field. Our Minor is closely integrated with our undergraduate research program, which places students in the labs of Bioinformatics faculty. Most of the Bioinformatics Minors at UCLA are working in a research lab.  Undergraduates are strongly encouraged to engage in research. The Minor allows for a substantial amount of research credits, an allowance that helps students complete their Major and Minor requirements in four years.  In addition, many of our undergraduates participate in the Bruins-in-Genomics Summer (B.I.G. Summer) program or similar undergraduate education experience summer programs.
  1. Bioinformatics is an Increasingly Diverse Field. The core courses in Bioinformatics are designed to be interesting and accessible to students from a wide variety of educational backgrounds. Each course typically has enrollment approaching 100. Far more students who are not in the Bioinformatics Minor take these courses as electives to fulfill their Major requirements. Student enthusiasm is high for these accessible interdisciplinary courses that combine computational sciences and Biology. We find that this approach boosts broader undergraduate engagement in the field and encourages students from traditionally underrepresented groups to pursue research, graduate school, or careers in STEM fields.
  1. Let Excitement Foster Program Growth. Bioinformatics is an exciting area, and specialized training is critical for the next generation of biomedical researchers. However, undergraduate Bioinformatics programs, when offered by a college or university, are typically quite small.  Such programs are often limited in size and engagement as students are unaware of the field or become aware of Bioinformatics late in their college career. We strategized the Bioinformatics Minor program at UCLA specifically to attract students at any stage of their college career and to maximize curricular flexibility so students can easily complete Minor requirements. Many students are attracted to the Minor when they enroll in Bioinformatics core courses to fulfill elective requirements for their Major; some develop a keen interest in the field and then join the Minor. Even students who are unable to complete all Minor requirements benefit from our program; they complete key coursework and join a research lab, gaining knowledge and experience crucial for gaining employment or admission to graduate school.

Our current goal for the Bioinformatics Minor is to graduate 50 students per year.  We hope that 10 to 20 of them will enter graduate studies in Bioinformatics.  We are not there yet, but are growing. This year, around 10 graduates applied to Ph.D. programs in Bioinformatics.  Many of our students recently began or are applying to Ph.D. programs in Bioinformatics and related areas.  We expect that they will do very well in the admissions process and have great backgrounds for starting Ph.D. study in Bioinformatics.

bioinformatics-minor-graphical-element-the-minor

Read more about the Bioinformatics Minor on the official website:
http://bioinformatics.ucla.edu/undergradute-bioinformatics-minor/

Check out a list of research opportunities available for undergrads at UCLA:
http://bioinformatics.ucla.edu/undergraduate-research/

Learn more about 2016 undergraduate research and B.I.G. Summer activities at ZarLab:
zarlab.cs.ucla.edu/b-i-g-summer-in-zarlab/

Applications to the 2017 B.I.G. Summer program are due January 27:
http://qcb.ucla.edu/big-summer/