About the Program
Under the auspices of the Center for Computational Biology, the Computational Biology Graduate Group offers the PhD in Computational Biology as well as the Designated Emphasis in Computational and Genomic Biology, a specialization for doctoral students in affiliated programs. The PhD is concerned with advancing knowledge at the interface of the computational and biological sciences, and is therefore intended for students who are passionate about being high functioning in both fields. The designated emphasis augments disciplinary training with a solid foundation in the different facets of genomic research, and provides students with the skills needed to collaborate across disciplinary boundaries to solve a wide range of computational biology and genomic problems.
Admissions
Admission to the University
Minimum Requirements for Admission
The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division:
- A bachelor’s degree or recognized equivalent from an accredited institution;
- A grade point average of B or better (3.0);
- If the applicant comes from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, 230 on the computer-based test, or an IELTS Band score of at least 7 (note that individual programs may set higher levels for any of these); and
- Sufficient undergraduate training to do graduate work in the given field.
Applicants Who Already Hold a Graduate Degree
The Graduate Council views academic degrees not as vocational training certificates but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without need to enroll in a related or similar graduate program.
Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field.
Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field.
The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines:
- Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics.
- Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved.
Applicants may apply only to one single degree program or one concurrent degree program per admission cycle.
Any applicant who was previously registered at Berkeley as a graduate student, no matter how briefly, must apply for readmission, not admission, even if the new application is to a different program.
Required Documents for Applications
- Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. If the applicant is admitted, then official transcripts of all college-level work will be required. Admitted applicants must request a current transcript from every post-secondary school attended, including community colleges, summer sessions, and extension programs. Official transcripts must be in sealed envelopes as issued by the school(s) attended. If you have attended Berkeley, upload your unofficial transcript with your application for the departmental initial review. If you are admitted, an official transcript with evidence of degree conferral will not be required.
- Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, not the Graduate Division.
- Evidence of English language proficiency: All applicants from countries or political entities in which the official language is not English are required to submit official evidence of English language proficiency. This applies to applicants from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement: 1) courses in English as a Second Language, 2) courses conducted in a language other than English, 3) courses that will be completed after the application is submitted, and 4) courses of a non-academic nature. If applicants have previously been denied admission to Berkeley on the basis of their English language proficiency, they must submit new test scores that meet the current minimum from one of the standardized tests.
Where to Apply
Visit the Berkeley Graduate Division application page .
Admission to the Program
Applicants for the Computational Biology PhD are expected to have a strong foundation in the basic sciences (e.g., biology, mathematics, chemistry), in addition to training in computing/informatics, significant programming experience, and substantial research experience. Typical students admitted to the program have demonstrated outstanding potential as a research scientist and have clear academic aptitude in multiple disciplines, as well as excellent communication skills. This is assessed based on research experience, grades, standardized exams, course selection, essays, personal background, and letters of recommendation. Three letters of recommendation are required, as is the general GRE. A GRE subject examination in an appropriate area is recommended, but not required. The program does not accept applicants interested in a Master of Science in Computational Biology.
Doctoral Degree Requirements
Normative Time Requirements
Normative Time to Advancement: Two years
Year 1
Students perform three laboratory rotations with the chief aim of identifying a research area and thesis laboratory. They also take courses to advance their knowledge in their area of expertise or fill in gaps in foundational knowledge. With guidance from the program, students are expected to complete six total courses by the end of the first or second year.
Year 2
Students attend seminars, prepare a dissertation prospectus, complete course requirements, and prepare for their PhD oral qualifying examination. With the successful passing of the orals, students select their thesis committee and advance to candidacy for the PhD degree.
Normative Time in Candidacy: Three years
Years 3 to 5
Students undertake research for the PhD dissertation under a four-person committee in charge of their research and dissertation. Students conduct original laboratory research, and then write the dissertation based on the results of this research. On completion of the research and approval of the dissertation by the committee, the students are awarded the doctorate.
Total Normative Time: 5-5.5 years
Time to Advancement
Curriculum
Courses Required | ||
CMPBIO 201 | Classics in Computational Biology | 3 |
CMPBIO 294A | Introduction to Research in Computational Biology | 2-12 |
CMPBIO 294B | Introduction to Research in Computational Biology | 2-12 |
Three graduate Foundation electives, as per core list, in consultation with the faculty advising committee: | 12 | |
At least one in biological sciences | ||
At least one in informatics | ||
Two graduate electives, as per core list, in consultation with the faculty advising committee, from course offerings in Molecular and Cell Biology, Bioengineering, Physics, Computer Science, Statistics, Public Health, Mathematics, Integrative Biology, Chemistry, and Plant & Microbial Biology | 8 | |
Three related graduate seminars | 12 | |
MCELLBI 293C | Responsible Conduct, Rigor and Reproducibility in Research | 1 |
Lab Rotations
Students conduct three 10-week laboratory rotations in the first year. The thesis lab, where dissertation research will take place, is chosen at the end of the third rotation in late April/early May.
Prospectus
The prospectus will include a description of the specific research problem, but will serve as a framework for the QE committee members to probe the student’s foundational knowledge in the field and area of research. Proposals will be written in the manner of a NIH-style grant proposal. The prospectus must be completed and submitted to the chair no fewer than four weeks prior to the oral qualifying examination.
Qualifying Examination
The qualifying examination will evaluate a student’s depth of knowledge in his or her research area, breadth of knowledge in fundamentals of computational biology, ability to formulate a research plan, and critical thinking. Students are expected to pass the qualifying examination by the end of the fourth semester in the program.
Time in Candidacy
Advancement
After passing the qualifying exam by the end of the second year, students have until the fifth semester to select a thesis committee and submit the Advancement to Candidacy paperwork to the Graduate Division.
Dissertation
Primary dissertation research is conducted in years 3-5/5.5. Requirements for the dissertation are decided in consultation with the thesis adviser and thesis committee members. To this end, students are required to have yearly thesis committee meetings with the committee after advancing to candidacy.
Dissertation Presentation/Finishing Talk
There is no formal defense of the completed dissertation; however, students are expected to publicly present a talk about their dissertation research in their final year.
Required Professional Development
Presentations
All computational biology students are expected to attend the annual retreat, and will regularly present research talks there. They are also encouraged to attend national and international conferences to present research.
Teaching
Computational biology students are required to teach two semesters, and may teach more. The requirement can be modified if the student has funding that does not allow teaching.
Designated Emphasis Requirements
Curriculum/Coursework
To qualify for the designated emphasis students must demonstrate competency by completing coursework, with a grade of B or better, in three of five areas: biology; computer science and engineering; chemistry, chemical engineering, and physics; biostatistics, mathematics, and statistics; and computational biology. Students with backgrounds in biology are expected to demonstrate competency in informatics (e.g., statistics, mathematics, computer science), and vice versa for students with quantitative backgrounds. Course lists are available on the CCB website (http://ccb.berkeley.edu/decgb ). Prior coursework may be used to fulfill requirements if the courses are comparable.
Qualifying Examination
The qualifying examination committee must include at least one, but preferably two, faculty members from the Computational Biology Graduate Group. The faculty member(s) may either represent the home department or serve as an outside member. Satisfactory performance on the qualifying examination for the doctorate will be judged independently from the designated emphasis.
Dissertation
The dissertation committee must include at least one, but preferably two, faculty members from the Computational Biology Graduate Group.
Courses
Computational Biology
CMPBIO 201 Classics in Computational Biology 3 Units
Terms offered: Fall 2017, Fall 2016, Fall 2015
Research project and approaches in computational biology. An introducton to the diverse ways biological problems are investigated computationally through critical evaluation of the classics and recent peer-reviewed literature. This is the core course required of all Computational Biology graduate students.
Rules & Requirements
Prerequisites: Acceptance in the Computational Biology Phd program; consent of instructor
Hours & Format
Fall and/or spring: 15 weeks - 1 hour of lecture and 2 hours of discussion per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
CMPBIO 290 Special Topics - Computational Biology 1 - 4 Units
Terms offered: Spring 2017, Spring 2016, Spring 2015
A graduate seminar class in which students closely examine recent computational methods in molecular and systems biology, for example for modeling mechanisms related to the regulation of gene expression and/or high-throughput sequencing data. The course will focus on computational methodology but will also cover relevant and interesting biological applications.
Rules & Requirements
Prerequisites: Graduate standing in EECS, MCB, Computational Biology or related fields; or consent of the instructor
Repeat rules: Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 1-3 hours of lecture per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
Instructor: Yosef
CMPBIO 293 Doctoral Seminar in Computational Biology 2 Units
Terms offered: Fall 2017, Spring 2017, Fall 2016
This one-year interactive seminar builds skills, knowledge and community in computational biology for first year PhD and second year Designated Emphasis students. Topics covered include concepts in human genetics/genomics, laboratory methodologies and data sources for computational biology, workshops/instruction on use of various bioinformatics tools, critical review of current research studies and computational methods, preparation for success in the PhD program and career development. Faculty members of the graduate program in computational biology and scientists from other institutions will participate. Topics will vary each semester.
Rules & Requirements
Repeat rules: Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 2 hours of seminar per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
CMPBIO 294A Introduction to Research in Computational Biology 2 - 12 Units
Terms offered: Fall 2017, Fall 2016, Fall 2015
Closely supervised experimental or computational work under the direction of an individual faculty member; an introduction to methods and research approaches in particular areas of computational biology.
Rules & Requirements
Prerequisites: Standing as a Computational Biology graduate student
Repeat rules: Course may be repeated for credit. Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 2-20 hours of laboratory per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
CMPBIO 294B Introduction to Research in Computational Biology 2 - 12 Units
Terms offered: Spring 2017, Spring 2016, Spring 2015
Closely supervised experimental or computational work under the direction of an individual faculty member; an introduction to methods and research approaches in particular areas of computational biology.
Rules & Requirements
Prerequisites: Standing as a Computational Biology graduate student
Repeat rules: Course may be repeated for credit. Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 2-20 hours of laboratory per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
CMPBIO 295 Individual Research for Doctoral Students 1 - 12 Units
Terms offered: Fall 2017, Summer 2017 10 Week Session, Spring 2017
Laboratory research, conferences. Individual research under the supervision of a faculty member.
Rules & Requirements
Prerequisites: Acceptance in the Computational Biology PhD program; consent of instructor
Repeat rules: Course may be repeated for credit. Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 1-20 hours of laboratory per week
Summer: 10 weeks - 1.5-30 hours of laboratory per week
Additional Details
Subject/Course Level: Computational Biology/Graduate
Grading: Letter grade.
CMPBIO 477 Introduction to Programming for Bioinformatics Bootcamp 1.5 Unit
Terms offered: Summer 2017, Summer 2015 3 Week Session
The goals of this course are to introduce students to Python, a simple and powerful programming language that is used for many applications, and to expose them to the practical bioinformatic utility of Python and programming in general. The course will allow students to apply programming to the problems that they face in the lab and to leave this course with a sufficiently generalized knowledge of programming (and the confidence to read the manuals) that they will be able to apply their skills to whatever projects they happen to be working on.
Rules & Requirements
Prerequisites: This is a graduate course and upper level undergraduate students can only enroll with the consent of the instructor
Hours & Format
Summer: 3 weeks - 40-40 hours of workshop per week
Additional Details
Subject/Course Level: Computational Biology/Other professional
Grading: Offered for satisfactory/unsatisfactory grade only.
Faculty and Instructors
Faculty
Doris Bachtrog, Associate Professor. Evolution of sex and recombination, Y degeneration, dosage compensation, sexually antagonistic variation.
Research Profile
Lisa F. Barcellos, Associate Professor. Public health, genetic epidemiology, human genetics, autoimmune diseases, multiple schlerosis, lupus erythematosus, rheumatoid arthritis, epigenetics, genomics, computational biology.
Research Profile
Steven Brenner, Professor. Molecular biology, computational biology, evolutionary biology, bioengineering, structural genomics, computational genomics, cellular activity, cellular functions, personal genomics.
Research Profile
Sandrine Dudoit, Professor. Genomics, classification, statistical computing, biostatistics, cross-validation, density estimation, genetic mapping, high-throughput sequencing, loss-based estimation, microarray, model selection, multiple hypothesis testing, prediction, RNA-Seq.
Research Profile
Michael B. Eisen, Professor. Genomics, genome sequencing, bioinformatics, animal development.
Research Profile
Oskar Hallatschek, Assistant Professor.
Haiyan Huang, Associate Professor. Applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification.
Research Profile
Nicholas Ingolia, Assistant Professor. Ribosome Profiling, translation, genomics.
Research Profile
Michael I. Jordan, Professor. Computer science, artificial intelligence, bioinformatics, statistics, machine learning, electrical engineering, applied statistics, optimization.
Research Profile
Rasmus Nielsen, Professor. Statistical and computational aspects of evolutionary theory and genetics.
Research Profile
Lior Pachter, Professor. Mathematics, applications of statistics, combinatorics to problems in biology.
Research Profile
Jasper D. Rine, Professor. Biology, cell biology, DNA replication, gene regulation, saccharomyces cerevisiae, genetic analysis, genome, cholesterol biosynthetic pathway, modification of proteins, prenylated proteins.
Research Profile
Kimmen Sjolander, Professor. Computational biology, algorithms, phylogenetic tree reconstruction, protein structure prediction, multiple sequence alignment, evolution, bioinformatics, hidden Markov models, metagenomics, statistical modeling, phylogenomics, emerging and neglected diseases, machine-learning, genome annotation, metagenome annotation, systems biology, functional site prediction, ortholog identification.
Research Profile
Contact Information
Computational Biology Graduate Group
574 Stanley Hall
Phone: 510-642-0379
Fax: 510-666-3399
Department Chair
Steven Brenner, PhD (Plant and Microbial Biology)
461A Koshland Hall
Phone: 510-643-9131
Head Graduate Adviser
Lisa Barcellos, PhD (Public Health)
324 Stanley Hall
Phone: 510-642-7814
Graduate Program Coordinator
Kate Chase
574 Stanley Hall, MC 3220
Phone: 510-642-0379
Administrative Director, CCB
Xuan Quach
174 Stanley Hall MC#3220
Phone: 510-666-3342
Fax: 510-666-3399