Course descriptions: Other courses of interest to Graduate Students in Biological Sciences
Chemistry C3079x-C3080y Physical chemistry, I and II. 4 pts. MWF 11-11:50.
(The first semester is required for Biology graduate students who have not had Physical Chemistry as undergraduates).
Prerequisites: CHEM C1403-C1404 or C3045-C3046; PHYS C1401-C1402, or the equivalent; MATH V1101-V1102 or V1105-V1106. Recommended parallel: CHEM C3085-C3086. An elementary but comprehensive treatment of the fundamental laws governing the behavior of individual atoms and molecules and collections of them.
Syllabus for Physical Chemistry C3079x Fall
The physical chemistry course was revised in 1999 to take into account the interests of its students, the great majority of whom are biochemistry majors, biology majors or chemistry majors who are premeds. The text is PHYSICAL CHEMISTRY:Principles and Applications in Biological Sciences. The writing is sparkling with many applications to biology. The authors are three expert biophysical chemists from Berkeley: Tinoco, Sauer and Wang. The Fall semester will be taught by Richard Bersohn and the Spring by Ken Eisenthal. The course is not a course in biochemistry or even biophysical chemistry. Thermodynamics will be taught in the Fall Semester. The lectures in the fall semester will be based on the following chapters:
Chapter 1. Introduction
Chapter 2. The First Law: Energy is Conserved.
Chapter 3. The Second Law: The Entropy of the Universe Increases
Chapter 4. Free Energy and Chemical Equilibria
Chapter 7. Kinetics: Rates of Chemical Reactions
Chapter 8. Enzyme Kinetics
Biology-Chemistry G4170y Biophysical
chemistry 4.5 pts. A. McDermott. Lecture: MWF 9:10-10:25.
(This course is not a substitute for Physical Chemistry)
Lab: M 7-10 evening. Prerequisite: elementary physical and organic chemistry.
Recommended preparation: elementary biochemistry. Tactics and techniques for the study of large molecules of biological importance; analysis of the conformation of proteins and nucleic acids; hydrodynamic, scattering, and spectroscopic techniques for examining macromolecular structure.
Chemistry G4172. Bioorganic
topics. 4.5 pts. R. Breslow. Prerequisite: introductory organic chemistry.
Recommended preparation: advanced organic chemistry. Not offered in 1995-96. Various topics in bioactive molecules in the field centered on natural-products chemistry, metabolic transformations, and enzyme mechanisms. Biosynthesis of natural products and some other bioorganic topics.
(A course in Statistics or Biostatistics is recommended for those biology graduate students students who have had only 2 semesters of college-level mathematics)
Students who do not know calculus or who want only a one-term course should take STAT W1001 or W1111. Note: Credit can be received for only one of these courses. All courses except STAT C3997 satisfy the science requirement. If there is any doubt about the appropriate course, a member of the department should be consulted. In the listing below, the designator STAT (Statistics) is understood to precede all course numbers for which no designator is indicated. The following designators appear in abbreviated form: PUBH (Public Health) and SIEO (Statistics-Industrial Engineering and Operations Research).
Statistics W1001x or y Introduction
to statistical reasoning 3 pts.
x: V. de la Peņa.TuTh 10:35-11:50. y: Instructor to be announced. TuTh 10:35-11:50.
Prerequisite: some high school algebra.
An introduction to the main ideas and tools of statistics emphasizing conceptual understanding and applications. The topics covered include: data collection and design of experiments, graphical methods of displaying data, probability and modeling, use of normal curve and its approximations, linear regression, estimation, confidence intervals, hypothesis testing, and computer use for data management. Examples are drawn from several areas of human knowledge including: medical studies, genetics, political science, social science, economics, population surveys, U.S. census, legal studies, marketing and business, physics, biological science. It may be used for partial fulfillment of the science requirement.
Statistics W1111x or y Introduction
to statistics, A 3 pts.
x: Sec 1: A. Gelman. TuTh 10:35-11:50. y: Sec 1: Instructor to be announced. TuTh 10:35-11:50. x and y: Sec 2: Instructor to be announced. MW 10:35-11:50. Sec 3: Instructor to be announced. TuTh 6:10-7:25 evening. Sec 4: Instructor to be announced. MW 6:10-7:25 evening. Sec 5: Instructor to be announced. TuTh 1:10-2:25. Sec 6: Instructor to be announced. MW 1:10-2:25.
Prerequisite: high school mathematics through intermediate algebra. Enrollment limited to 45 students.
Designed for students in fields (such as economics) that emphasize quantitative methods. Probability concepts and basic theory of sampling distributions are used as aids to quantitative reasoning and data analysis, with illustrations drawn from the natural and social sciences. Problems of data quality and causal inference; graphical and numerical summaries of data; statistical modeling of relationships between variables; use of computers for data management, evaluation of models, and estimation of parameters.
Statistics W1211x or y Introduction
to statistics, B 3 pts.
x: P. Meier. y: Instructor to be announced. x and y: TuTh 6:10-7:25 evening.
Prerequisite: Calculus I.
Designed for students in fields that emphasize quantitative methods. Probability concepts and basic theory of sampling distributions are used as aids to quantitative reasoning and data analysis, with illustrations drawn from the natural and social sciences. Introduction to use of computers for data management, graph construction, evaluation of regression models, and estimation of unknown parameters. Topics of STAT W1111 are covered in greater depth.
Public Health P6103 Introduction to
This course covers the language of biostatistics and the standard techniques of data collection and analysis. It is designed as a first semester course and includes topics discussed in Public Health P6100. The inferential topics include the Normal distribution, measures of central tendency and despersion, hypothesis testing, confidence intervals, regression and correlation.