Rainer Sachs, Professor

Closed (1) Modeling cancer risk for astronauts on Mars missions or other extended voyages above low earth orbit.

Applications for Fall 2017 are now closed for this project.

I am interested in mathematical and computer modeling of the carcinogenesis process, particularly of cancers due to ionizing radiation. We are analyzing cancers produced when astronauts encounter galactic cosmic rays (GCR). GCR occur almost exclusively outside of what NASA terms low earth orbit. This high energy radiation realistically cannot be shielded against. We are using in silico modeling to estimate how dangerous GCR are. We are using modern mathematical synergy analysis to plan and interpret experiments at Brookhaven National Laboratory on the tumorigenic risk to mice of a mixed radiation field, and on the effect of such fields on cancer surrogate endpoints such as chromosome aberrations, using results of experiments on each individual radiation in the mixture.

We will meet for an hour a week to discuss progress. At least six hrs/week of work would be needed, mostly at your own time on your own computer. Students are required to sign up for URAP. However they may choose to take 0 hours, which avoids using up units needed for other courses. In many cases the primary result will be a broadening of the student's perspective. However, sometimes a student coauthorship on a published paper results. I believe the URAP program should be primarily for the education of the student, not for the convenience of the faculty members, but some routine tasks will be part of the assignments. There will be no specific benchmarks students have to meet, other than utilizing their strengths and filling in gaps in their knowledge and their mathematical/computational expertise.

Applied mathematicians typically find it much easier to do formal calculations than to gain a reasonable perspective on what calculations are useful. I hope the proposed project will help a hard-science major gain expertise in biomedical applications.

Qualifications: My best results with URAP have come when students try a project one semester and then choose to continue. Therefore I will prefer students whose anticipated graduation date is Jan 2019 or later though of course you don't need to commit to more than one semester now. This is an opportunity for students with backgrounds in applied math, statistics, computer science, pure math, physics, chemistry, or MCB to apply their knowledge to cancer biology. The student should be familiar with computer programming in R and must give details of how much R they know in their application. The student should also have one calculus-based course in probability or statistics. Very desirable but not essential: good understanding of lower division material on non-linear first order odinary differential equations; upper division probability and statistics course(s). Grades in STEM courses should average A- or better, preferably with at least one A+. Lower division students should have mainly A and A+ grades in technical courses. Desirable: upper division courses in MCB. Because of the interdisciplinary nature of the projects, many students might need some extra background. In that case the first half of the semester would be devoted to rounding off the student's expertise and the second half would involve some calculations.

Weekly Hours: 6-9 hrs

Off-Campus Research Site: apart from weekly meetings most of the work will be done by the student at home or anywhere else the student finds convenient.

Related website: http://math.berkeley.edu/~sachs/index.html

Closed (2) Synergy modeling in pharmacology: a new mathematical approach

Applications for Fall 2017 are now closed for this project.

For well over a century biologists and medical researchers have been studying effects of two or more agents, such as therapeutic drugs, when these agents are applied simultaneously. A number of different ways have been suggested to obtain a default hypothesis about the dose-response of a given agent mixture from the dose-response of the individual components of the mixture, deviations from the default being then characterized as synergy or antagonism of the components. The different suggestions are not consistent and choosing between them remains controversial even now. Such questions arise in various fields, e.g. in pharmacometrics, in analyzing stressors in evolutionary ecology, in analyzing combinations of harmful substances in toxicology; etc..
Working for NASA on carcinogenic effects of the unusual ionizing radiation types that occur only outside of low earth orbit, cannot be shielded against in practice, and may be unexpectedly toxic, my group has found a better way to formulate the default hypothesis which relates mixture effects to the effects of its components. The project is to apply this new formalism to some simulated pharmacological data, or to real data in the literature, and compare its accuracy with that of the older methods.

See project 1

Qualifications: See project 1

Weekly Hours: 6-9 hrs

Off-Campus Research Site: Apart from weekly 1 hour meetings most of the work will be done by the student at home or anywhere else the student wants to use his/her laptop and the internet.

Related website: http://math.berkeley.edu/~sachs/index.html
Related website: http://dx.doi.org/10.1667/RR14411.1.S1

Related website: http://math.berkeley.edu/~sachs/index.html (out of date)