Computational and Systems Biology BS

Overview

Computational and Systems Biology majors select a coherent integration of courses from one of five designated concentrations: bioinformatics, biological data sciences, biomedical systems, neurosystems, or systems biology. The synergy for all concentrations is integrative systems, information, and computational systems modeling sciences in biology. The focus is primarily quantitative, as mastery … For more content click the Read More button below. The bioinformatics concentration is designed for students interested in computational discovery and management of biological data, primarily genomic, proteomic, or metabolomic data. Bioinformatics emphasizes computational, statistical, and other mathematical approaches for mining, modeling, and analyzing high-throughput biological data and the inherent structure of biological information. Example research problems include finding statistical patterns that reveal genomic or evolutionary or developmental information, studying how regulatory sequences give rise to programs of gene expression, or researching how the genome encodes the capabilities of the human mind. The biological data sciences concentration addresses a diverse set of biological questions—ranging from medicine, to genomics, physiology, pharmacology, neuroscience, ecology, and evolution—using recent tools and advances in mathematics and computation—specifically machine learning, statistical data sciences, and informatics. Biological data sciences leverages new and developing courses within computational and systems biology and across UCLA, and greatly aids students who aim to go directly into industry—biotech, pharmaceuticals, and more—as well as computational biology graduate school. The concentration has a strong focus and deep integration with life sciences. The biomedical systems concentration is designed for students interested primarily in medical system studies; the systems aspects of biomedical, surgical, or other biomedical engineering system devices including MEMS or nanoscale system devices; and use of dynamic biosystem modeling for optimizing or developing new clinical diagnostic or therapeutic protocols. Example research problems include feedback biocontrol system model development for imaging-based medical diagnosis and optimal control of therapeutic drug delivery. The neurosystems concentration is designed for students interested primarily in the nervous system, or quantitative neurophysiology, with emphasis on neural system networks that control behavior at molecular, cellular, and whole-organism levels; neural information and control systems; and systems electrophysiology and neural electronic systems for controlling prostheses. Example research problems include analysis of (real) neural networks in normal and abnormal brain function, design of prosthetic systems for hearing (cochlear implant) and walking (spinal cord stimulation) recovery, and MEMS-based brain-machine interface devices. The systems biology concentration is designed for students who want to understand biological systems holistically and quantitatively, and pursue research with an emphasis on systems and integrative principles in biology or medicine. The curriculum imparts an understanding of systems biology (often called the new physiology) using dynamical systems modeling, control, computer simulation, and other computational methods—integrated with the biology. For example, at the cellular level, systems biologists integrate proteomic, transcriptomic, and metabolomic information into a more complete systems picture of living organisms. However, the methodologies include single-scale or multiscale modeling for enhancing understanding of regulatory biomechanisms at all levels—molecular, cellular, organ, and/or whole-organism levels—and are prevalent in population and ecosystem studies, as well as systems-level problems in medicine and pharmacology.

The bioinformatics concentration is designed for students interested in computational discovery and management of biological data, primarily genomic, proteomic, or metabolomic data. Bioinformatics emphasizes computational, statistical, and other mathematical approaches for mining, modeling, and analyzing high-throughput biological data and the inherent structure of biological information. Example research problems include finding statistical patterns that reveal genomic or evolutionary or developmental information, studying how regulatory sequences give rise to programs of gene expression, or researching how the genome encodes the capabilities of the human mind.

The biological data sciences concentration addresses a diverse set of biological questions—ranging from medicine, to genomics, physiology, pharmacology, neuroscience, ecology, and evolution—using recent tools and advances in mathematics and computation—specifically machine learning, statistical data sciences, and informatics. Biological data sciences leverages new and developing courses within computational and systems biology and across UCLA, and greatly aids students who aim to go directly into industry—biotech, pharmaceuticals, and more—as well as computational biology graduate school. The concentration has a strong focus and deep integration with life sciences.

The biomedical systems concentration is designed for students interested primarily in medical system studies; the systems aspects of biomedical, surgical, or other biomedical engineering system devices including MEMS or nanoscale system devices; and use of dynamic biosystem modeling for optimizing or developing new clinical diagnostic or therapeutic protocols. Example research problems include feedback biocontrol system model development for imaging-based medical diagnosis and optimal control of therapeutic drug delivery.

The neurosystems concentration is designed for students interested primarily in the nervous system, or quantitative neurophysiology, with emphasis on neural system networks that control behavior at molecular, cellular, and whole-organism levels; neural information and control systems; and systems electrophysiology and neural electronic systems for controlling prostheses. Example research problems include analysis of (real) neural networks in normal and abnormal brain function, design of prosthetic systems for hearing (cochlear implant) and walking (spinal cord stimulation) recovery, and MEMS-based brain-machine interface devices.

The systems biology concentration is designed for students who want to understand biological systems holistically and quantitatively, and pursue research with an emphasis on systems and integrative principles in biology or medicine. The curriculum imparts an understanding of systems biology (often called the new physiology) using dynamical systems modeling, control, computer simulation, and other computational methods—integrated with the biology. For example, at the cellular level, systems biologists integrate proteomic, transcriptomic, and metabolomic information into a more complete systems picture of living organisms. However, the methodologies include single-scale or multiscale modeling for enhancing understanding of regulatory biomechanisms at all levels—molecular, cellular, organ, and/or whole-organism levels—and are prevalent in population and ecosystem studies, as well as systems-level problems in medicine and pharmacology.

Capstone Major

The Computational and Systems Biology major is a designated capstone major. The capstone experience is a senior-level sequence of two courses integrating the discipline via mathematical modeling, simulation, and active research and report writing. Students are expected to demonstrate critical thinking skills and familiarity with research techniques needed to successfully pursue a research project in computational and systems biology, conceive and execute a research project on which they engage current methods and theory, communicate original scholarly findings to peers both in oral and written form, and work productively with others as part of a research team. The experience culminates with completion of the senior thesis requirement.

Learning Outcomes

Demonstrated critical thinking skills, and familiarity with research techniques, needed to successfully pursue a research project

Conception and execution of a research project that engages current methods and theory

Oral and written communication of original scholarly findings to peers

Productive participation with others as part of a research team

Entry to the Major

Pre-Major

Students entering UCLA directly from high school or first-term transfer students who declare the Computational and Systems Biology pre-major at the time of application are automatically admitted.

Current students who were admitted as first-year or transfer students (transfer students must have been admitted under the division of life sciences) may request to declare the pre-major once they have met the following criteria: (1) completed one quarter at UCLA, (2) are in good academic standing, (3) have a minimum cumulative grade-point average (GPA) of 2.0, and (4) have established a pre-major GPA of a minimum of 2.7 by taking at least one pre-major course at UCLA for a letter grade.

Requests to declare the pre-major should be sent by e-mail to the program . For more information, see the program website.

All courses taken for the pre-major must be completed with a grade of C or better. Pre-major courses Program in Computing 10B and 10C, or Computer Sciences 32 are required for students following the Biological Data Sciences or Bioinformatics concentrations, but do not have to be completed prior to applying to the major. Computational and Systems Biology M32 or Mathematics 32A is required for students following the Bioinformatics, Biomedical Systems, or Systems Biology concentrations, but does not have to be completed prior to applying to the major.

All students are identified as pre-majors until they satisfy the preparation for the major requirements by achieving (1) a minimum 2.7 GPA in all pre-major courses, and (2) a minimum grade of C in all pre-major courses.

Transfer Students

Transfer applicants to the Computational and Systems Biology major with 90 or more units must complete as many of the following introductory courses as possible prior to admission to UCLA: one year of general chemistry with laboratory for majors, two years of calculus for majors, one year of calculus-based physics, one year of biology with laboratory for majors, and one programming course using C++ , Python, or similar language.

Transfer applicants must meet the same academic requirements as current UCLA students, based on all courses transferred from another institution that satisfy pre-major requirements, and must have completed one 12-unit term of residence in regular session at UCLA.

Refer to the UCLA transfer admission guide for up-to-date information regarding transfer selection for admission.

Major Requirements

Preparation for the Major

A minimum of 66 to 82 units (depending on the calculus series, computer programming courses, and additional requisites for specific concentrations). Additional lower-division courses may be requisite to desired track courses.

Chemistry

Computer Science or Program in Computing

Life Sciences

Mathematics

Complete 5 to 6 courses total from one of the following options:

Life Sciences

Students may select Computational and Systems Biology M32 or Mathematics M32T.

Mathematics

Physics

Select one series from:

Physics 1 series

Physics 1 Honors series

Physics 5 series

Additional Courses by Track

Additional preparation for the major courses are required for the following tracks:

Bioinformatics

Biological Data Science

The Major

The major consists of a methodology core of seven courses (27 units) and a track of five upper-division courses (20 units minimum).

Methodology Core

Complete three required courses, one probability course, one statistics course, and two capstone courses as follows:

Probability

Statistics

Capstone

Select one option from:

Computational and Systems Biology M187 and 195

Complete the following two courses:

Computational and Systems Biology M187 and 199

Complete the following two courses:

Computational and Systems Biology 198A and 198B

Complete the following two courses:

Tracks

Complete a minimum of five courses (20 units minimum) from the following tracks. No 199 course may be applied toward any track.

Bioinformatics (at least 20 units)

Note: Computer Science 32 or Program in Computing 10B and 10C, and Computational and Systems Biology M32 (same as Life Sciences M32 or Mathematics M32T) or Mathematics 32A are completed in the pre-major.

Computer Science

Select one course from:

Additional Courses

Select two courses from:

Life Science Courses

Select two life science courses from the life sciences course list.

Biological Data Sciences (at least 20 units)

Note: Computer Science 32 is completed in the pre-major. A maximum of two courses may be from mathematics.

Additional Courses

Select three courses (at least 20 units) from the following. Only one course from Computer Science CM124 or M226 may be applied. Only one course from Computer Science M146, Mathematics 156, or Statistics C161 may be applied. Only one course from Computer Science 180 or Mathematics 182 may be applied.

Life Science Courses

Select two life science courses from the life sciences course list.

Dynamical Modeling (at least 20 units)

A maximum of two courses may be from mathematics.

Additional Courses

Select three courses from the following list. Only one course from Computational and Systems Biology M186 or Computer Science M182 may be applied. Only one course from Mathematics 134 or 135 may be applied.

Life Science Courses

Select two life science courses from the life sciences course list.

Life Science Course List (for all three tracks)

Select any two courses from the subareas. Courses may be chosen from different subareas.

Biochemistry

Ecology

Epidemiology

Genetics and Molecular Biology

Only one course from Molecular, Cell, and Developmental Biology 100 or 165A may be applied.

Neurosystems

Only one course from Neuroscience M101A or Psychology 115 may be applied.

Physiology

Only one course from Ecology and Evolutionary Biology 170 or Physiological Sciences 166 may be applied.

General Catalog 2022-23