Overview
Computational biology is an academic growth area that binds together multiple areas of biological research with the mathematical and computational sciences. It takes center stage in the new data-oriented biology by facilitating scientific discoveries based on high-throughput methods. The genomic revolution has fundamentally changed the biological sciences, and computational biology provides the means for translation of genomic discoveries into a new understanding of complex biological systems and eventually into improvements of the human condition through development of solutions to environmental problems, new drug discoveries, and personalized medicine.
The Center for Computational Biology is Berkeley’s hub for research and training in computational biology and bioinformatics. Through courses, seminars, scientific meetings, and innovative training programs for PhD students administered by the Graduate Group in Computational Biology, the center catalyzes biological discoveries at the interface of biology, computation, and mathematics/statistics. As a campus strategic initiative, the center fosters an interactive, innovative, and collegiate environment for faculty, students, and postdoctorates drawn from five colleges and over a dozen academic departments. Faculty research interests are likewise diverse, ranging from computational and statistical genomics to population, comparative, and functional genomics; from bioinformatics and proteomics to evolutionary biology, phylogenomics, and statistical and computational methods development for modeling biological systems.
Undergraduate Programs
There is no undergraduate program in Computational Biology.
Graduate Programs
Computational Biology : Designated Emphasis (DE), PhD
Courses
Computational Biology
CMPBIO 98BC Berkeley Connect in Computational Biology 1 Unit
Terms offered: Fall 2017, Spring 2017, Fall 2016
Berkeley Connect is a mentoring program, offered through various academic departments, that helps students build intellectual community. Over the course of a semester, enrolled students participate in regular small-group discussions facilitated by a graduate student mentor (following a faculty-directed curriculum), meet with their graduate student mentor for one-on-one academic advising, attend lectures and panel discussions featuring department faculty and alumni, and go on field trips to campus resources. Students are not required to be declared majors in order to participate. Course may be repeated.
Rules & Requirements
Repeat rules: Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 1 hour of discussion per week
Additional Details
Subject/Course Level: Computational Biology/Undergraduate
Grading/Final exam status: Offered for pass/not pass grade only. Final exam not required.
Instructor: Nielsen
CMPBIO 175 Introduction to Computational Biology and Precision Medicine 3 Units
Terms offered: Summer 2017 Second 6 Week Session
Computational biology is an interdisciplinary field that develops and/or applies computational methods including bioinformatics to analyze large collections of biological data such as genomic data with a goal of making new predictions or discoveries. Precision medicine is an emerging approach for human disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. Computational biology and bioinformatics tools are critical for advancing precision medicine. This survey course introduces computational tools for the analysis of genomic data and approaches to understanding and advancing precision medicine.
Hours & Format
Summer: 6 weeks - 12 hours of lecture per week
Additional Details
Subject/Course Level: Computational Biology/Undergraduate
Grading/Final exam status: Letter grade. Alternative to final exam.
CMPBIO 198BC Berkeley Connect in Computational Biology 1 Unit
Terms offered: Fall 2017, Spring 2017, Fall 2016
Berkeley Connect is a mentoring program, offered through various academic departments, that helps students build intellectual community. Over the course of a semester, enrolled students participate in regular small-group discussions facilitated by a graduate student mentor (following a faculty-directed curriculum), meet with their graduate student mentor for one-on-one academic advising, attend lectures and panel discussions featuring department faculty and alumni, and go on field trips to campus resources. Students are not required to be declared majors in order to participate. Course may be repeated.
Rules & Requirements
Repeat rules: Course may be repeated for credit when topic changes.
Hours & Format
Fall and/or spring: 15 weeks - 1 hour of discussion per week
Additional Details
Subject/Course Level: Computational Biology/Undergraduate
Grading/Final exam status: Offered for pass/not pass grade only. Final exam not required.
Instructor: Nielsen
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
Adminstrative Director, CCB
Xuan Quach
174 Stanley Hall MC #3220
Phone: 510-666-3342
Fax: 510-666-3399