An overview of the Pellegrini Lab's studies in mice. Depicted at the top is DNA methylation data used to relate to metabolic traits.
Each June, thousands of UCLA students graduate and find themselves thrust out of the familiar university environment. Some have secured full-time jobs, others acceptance to graduate schools, and for many the path ahead is simply unknown. In the world of genetics, though, much of what's ahead can be scientifically-speculated directly out of the womb. And what's possible is rapidly expanding through the study of the genome, which is the complete set of genetic material present in a cell or organism.
Today, to get one's genome sequenced and analyzed costs about $1,000. In 2008, that cost was around $10 million. Mail order tests are now available to predict the genetic risk of diseases including breast and ovarian cancers to bipolar disorder to Parkinson's disease whereas 152 years ago the gene had not even been discovered. Read more here.
Our Technology Operations team has an outstanding technical leadership opportunity to oversee our Infrastructure Operations team. The Senior Manager, Infrastructure Operations is responsible for the management and oversight of mission-critical (24/7/365) operations related to UCLA's campus data center, mainframe systems, servers, storage systems, applications operations, enterprise messaging, and associated technical services. For position details and a list of desired qualifications, please visit our posting on the UCLA Career Opportunities website – Requisition #25388
Anders J. Askenas
UCLA Information Technology Services -- Human Resources
Wednesday, March 8
11:45 am to 1 pm
5628 Math Science -- The Portal
Abstract:
Dynamic recrystallization can be defined as a spontaneous change in the microstructure of a material during deformation at an elevated temperature due to the growth of defect-free grains through the motion of high angle grain boundaries. One of the most important uses of recrystallization is in metal processing, where recrystallized grains increase the ductility resulting in better control of the grain structure. On the other hand, it is undesirable from a design perspective, since recrystallization alters the microstructure resulting in a change in the material's macroscopic properties. In this talk, I will describe our ongoing work on modeling grain growth during recrystallization in the presence of external loads.
Dynamic recrystallization is a uniquely challenging phenomenon to model since the microstructure and the material deformation evolve at the same time scale. Grain boundary motion in the absence of deformation is commonly modeled using phase field models, while the deformation of a material with a fixed grain boundary structure is commonly modeled using crystal plasticity. In this work, we develop a thermodynamically consistent model which models deformation and grain growth simultaneously, thus enabling us to understand dynamic recrystallization. The highlight of this model is it is a non-classical gradient elastic model that can simulate various interesting phenomena observed in dynamic recrystallization, where a grain rotates to increase/decrease its misorientation as its grain boundary evolves. Register here.
Speaker:
Dr. Nikhil Chandra Admal is a postdoctoral research scholar working with Professor Jaime Marian in the Materials Science and Engineering department at UCLA. He is broadly interested in the multiscale modeling of materials at various lengths and time scales ranging from the atomic scale to the continuum scale. Currently, the focus of his research is on the study of recrystallization in refractory materials to increase their operating temperature, and development of first-principles strain gradient elastic models to include non-local effects relevant in micromechanical systems, and systems with defects.
Prior to joining UCLA, Dr. Admal obtained his Ph.D. from the Department of Aerospace Engineering and Mechanics at the University of Minnesota.
Tuesday, February 28
9 am - 12 pm
5628 Math Science -- The Portal
R is a powerful statistical package that runs on many platforms, including Windows, Macintosh and Unix. This class is designed for people who are just getting started using R. The students in the class will have a hands-on experience using R for statistics, graphics, and data management. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However, it is possible for individuals to use the class notes to help in learning R even if they don't enroll in the workshop. Register here.
Wednesday, March 1 through Friday, March 3
460 Portola Plaza
Institute for Pure & Applied Mathematics (IPAM)
Epigenetics refers to information transmitted during cell division other than the DNA sequence per se, and it is the language that distinguishes stem cells from somatic cells, one organ from another, and even identical twins from each other. In contrast to the DNA sequence, the epigenome is relatively susceptible to modification by the environment as well as stochastic perturbations over time, adding to phenotypic diversity in the population. Despite its strong ties to the environment, epigenetics has never been well reconciled to evolutionary thinking, and in fact there is now strong evidence against the transmission of so-called "epi-alleles," i.d. epigenetic modifications that pass through the germline.
However, genetic variants that regulate stochastic fluctuation of gene expression and phenotypes in the offspring appear to be transmitted as an epigenetic or even Lamarckian trait. Furthermore, even the normal process of cellular differentiation from a single cell to a complex organism is not understood well from a mathematical point of view. There is increasingly strong evidence that stem cells are highly heterogenous and in fact stochasticity is necessary for pluripotency. This process appears to be tightly regulated through the epigenome in development. Moreover, in these biological contexts, "stochasticity" is hardly synonymous with "noise," which often refers to variation which obscures a "true signal" (e.g., measurement error) or which is structural, as in physics (e.g., quantum noise). In contrast, "stochastic regulation" refers to purposeful, programmed variation; the fluctuations are random but there is no true signal to mask.
This workshop will serve as a forum for scientists and engineers with an interest in computational biology to explore the role of stochasticity in regulation, development and evolution, and its epigenetic basis. Just as thinking about stochasticity was transformative in physics and in some areas of biology, it promises to fundamentally transform modern genetics and help to explain phase transitions such as differentiation and cancer.
This workshop will include a poster session; a request for poster titles will be sent to registered participants in advance of the workshop. Register here.
Tuesday, March 7
9 am - 12 pm
5628 Math Science -- The Portal
This workshop introduces how to use the R ggplot2 package, particularly for data analysis accompanying a planned regression model. First, the underlying grammar (system) of graphics is introduced with demonstrations. Then the usage of ggplot2 for exploratory graphs, model diagnostics, and presentation of model results is illustrated through 3 examples. Register here.
Monday, March 6 through Friday, March 10
460 Portola Plaza
Institute for Pure & Applied Mathematics (IPAM)
The equations of gauge theory lie at the heart of our understanding of particle physics. The Standard Model, which describes the electromagnetic, weak, and strong forces, is based on the Yang-Mills equations. Starting with the work of Donaldson in the 1980s, gauge theory has also been successfully applied in other areas of pure mathematics, such as low dimensional topology, symplectic geometry, and algebraic geometry.
More recently, Witten proposed a gauge-theoretic interpretation of Khovanov homology, a knot invariant whose origins lie in representation theory. Khovanov homology is a "categorification" of the celebrated Jones polynomial, in the sense that its Euler characteristic recovers this polynomial. At the moment, Khovanov homology is only defined for knots in the three-sphere, but Witten's proposal holds the promise of generalizations to other three-manifolds, and perhaps of producing new invariants of four-manifolds.
This workshop will bring together researchers from several different fields (theoretical physics, mathematical gauge theory, topology, analysis / PDE, representation theory, symplectic geometry, and algebraic geometry, and thus help facilitate connections between these areas. The common focus will be to understand Khovanov homology and related invariants through the lens of gauge theory.
This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop. Register here.
The goal of the UCLA IDRE Statistical Consulting Group is to help UCLA faculty, staff, and graduate students perform top-notch research, with the greatest emphasis on data analysis related to grants and publications, but also including dissertation research. We provide advice and resources to enable you to develop and/or extend your statistical computing skills, helping you to independently use common statistical packages for the analysis of your research. Current hours for walk-in consulting are Monday-Thursday 12-3 PM.
Walk-in consulting is in Math Sciences 4919. See our online schedule for days and hours.
UCLA Office of Information Technology
Institute for Digital Research and Education
310-825-6635 | frontdesk@oit.ucla.edu https://idre.ucla.edu/
5308 Math Sciences
Box 951557, Mail Code 155705
Los Angeles, CA 90095-1557