Abstracts from CSGF Practicum Experience at
Lawrence Berkeley National Lab

Current Fellows
2009
	Eric Chi, Rice University Paul T Spellman, Life Sciences, Lawrence Berkeley National Lab 05/11/09-08/14/09 A Comparison of Helicos and Illumina RNA-sequencing platforms A collection of cancer cells can be distinguished by the relative abundance of its transcribed mRNA (transcriptome). Being able to distinguish such heterogeneity among Ovarian cancer cells for example would be an important step in developing targeted therapies to the various subtypes of ovarian cancer. It's possible to measure how much of each kind of mRNA is present in a cell through direct sequencing. There are different technologies with their own benefits and downsides. We compared two different sequencing approaches on a common set of ovarian cell and cell line samples to assess the technical effects (e.g. measurement biases) introduced by each vendor's approach.
	Ying Hu, Rice University James Schuck & Jeff Neaton, Molecular Foundry, Lawrence Berkeley National Lab 05/11/09-08/21/09 Engineering gold nanostructures for surface-enhanced Raman spectroscopy Title: Engineering gold nanostructures for surface-enhanced Raman spectroscopy In this project, we applied finite-element method to investigate the far-field and near-field optical properties of several nanostructures, including gold-silica-gold multilayer nanoshells, gold bowtie antennas, and gold substrates with ordered nanoclusters. The goal of the study is to explore effective designs of plasmonic nanostructures to achieve spectral and spatial localization of light at nanometer scale. The investigation bears potential applications in mind such as a color sorter and substrates for surface-enhancement Raman spectroscopy.
	Eric Liu, Massachusetts Institute of Technology Phillip Colella, Applied Numerical Algorithms Group, Lawrence Berkeley National Lab 06/01/09-08/21/09 Overall group: Chombo my work: Artificial Viscosity for 4th order accurate Finite Volume Schemes Chombo is a set of tools designed for solving partial differential equations in a fast, scalable manner using finite volume methods. Some of their major selling points include higher-order (4th) accurate solution methods, (automated) adaptive mesh refinement, multiblock mesh capability, cut-cells, and a high degree of scalability. Chombo is designed to be usable by scientists and engineers with complex modeling problems regardless of their level of experience with numerical methods. The package provides a framework for solving a large variety of problems ranging from fluid dynamics to electrodynamics and many things in between.
	Douglas Mason, Harvard University Peter Nugent, Computational Cosmology Center, Lawrence Berkeley National Lab 06/01/09-08/22/09 DeepSky In response to the needs of several astrophysics projects hosted at NERSC, Peter Nugent's group at LBNL is creating an all-sky digital image based upon the point-and-stare observations taken via the Palomar-QUEST Consortium and the SN Factory + Near Earth Asteroid Team. This data spans 9 years and almost 20,000 square degrees, with typically 10-100 pointing on a particular part of the sky. In total there are 11 million images. This data will be used to image and analyze stars with high proper motion, and to retrieve images of the stellar objects which precede supernovae and gamma-ray bursts.
	Britton Olson, Stanford University Phillip Colella, Computational Research Division, Lawrence Berkeley National Lab 06/22/09-09/14/09 Atmospheric Modeling using Chombo The Applied Numerical Algorithms Group (ANAG) at Lawrence Berkeley National Lab has been developing a library of Partial Differential Equation (PDE) software tools for use in a wide variety of applications. This software, CHOMBO, traditionally employed a 2nd order finite volume discretization coupled with a sophisticated Adaptive Mesh Refinement (AMR) scheme. More recently, this order has been extended to 4th order and the traditional rectilinear Cartesian grid, has been generalized to support structured curvilinear meshes. Finally, a multi-block capability is being added which enables non-aligning grids to interact. With the emergence of these new technologies, group leader Phillip Colella wanted to explore an application which employed all three. Atmospheric models of the stratified atmosphere traditionally solve whats known as the Shallow Water Equations. We set out to solve these equations on the surface of a sphere and determine the advantages for this particular model, or using a high-order scheme.
2008
	Tal Danino, University of California, San Diego Jay Keasling, Physical Biology, Lawrence Berkeley National Lab 09/10/08-02/01-09 Can yields of a biofuel candidate Isopentenol be increased using oscillatory promoters? In synthetically constructed pathways used to produce chemical compounds, biofuels, etc., inducible promoters are often used to drive various genes in a pathway. These promoters are constantly induced and are always producing mRNA transcripts and proteins during the lifetime of a cell. Constant production of transcripts can cause a high metabolic burden and therefore be detrimental to organism growth, and decrease yield of downstream products. Furthermore, certain products produced in a pathway can also be growth inhibiting or toxic, and therefore a switching between ON and OFF (such in an oscillatory system) of the responsible gene could improve pathway yield. If this is true, what will be the optimal period of oscillations used to drive these genes? I am working on answering this question by constructing various genes in a pathway under control of inducible and oscillatory promoters.
	Robin Friedman, Massachusetts Institute of Technology Jennifer A. Doudna, Physical Biosciences, Lawrence Berkeley National Lab 06/01/08-08/31/08 Computational Analysis of CRISPR Mechanism, Function, and Evolution CRISPRs (Clustered, Regularly Interspaced Short Palindromic Repeats) are arrays of direct sequence repeats surrounded by spacers, flanked by CRISPR-associated (cas) genes, that provide acquired resistance to phage. This system is widespread in both Archea and Bacteria, but little is known about its mechanism of action or the function of individual cas proteins. We set out to better characterize its function and mechanism by computational analysis of spacer targets, of the evolutionary properties of CRISPR-containing genomes, and of the sequence and structural homologs of cas proteins.
	Sarah Richardson, Johns Hopkins University School of Medicine Adam Arkin, Physical Biosciences Division, Lawrence Berkeley National Lab 06/02/08-08/29/09 The Design of Orthogonal Components for a Transcription Attenuation System The Staphylococcus aureus plasmid pT181 uses an RNA-based transcription attenuation system to control plasmid replication and copy number. The Arkin lab is studying and modifying this system for use as a synthetic and inducible transcription control system in Escherichia coli. Such a nucleotide-based system would allow a rapid, mutable, and fine-grained control of gene expression that is impossible to achieve with protein-based methods like transcription factors. If successful, their system will be characterized by modularity (it will be made up of defined, discrete and flexible pieces), transferability (the attenuator will work inside different organisms) predictability (its behavior under different conditions will be well understood), orthogonality (pieces of one attenuator will not interfere with pieces of another), and composability (several attenuators may be effectively chained in series or stacked in a cascade). These four points are axiomatic attributes of every component in an electrical circuit, and it is the Arkin group's hope that by reproducing them biologically they will be able to take advantage of the great body of knowledge and tools available to electrical engineers and apply it directly to the field of synthetic biology.
2007
	Peter Norgaard, Princeton University Phillip Colella, Computing Sciences Directorate, Lawrence Berkeley National Lab 06/04/07-08/31/07 Application of adaptive mesh refinement to particle-in-cell methods The applied numerical algorithms group at LBL has developed a software library known as Chombo for solving PDEs using the adaptive mesh refinement technique. The goal of my practicum project was to extend Chombo's capabilities to include the particle-in-cell method. In PIC, discrete charge carrying particles are allowed to move continuously in space, while the fields are solved at discrete grid points. As a necessary step, the charge from each particle must be assigned to the grid, and the force interpolated back to each particle. The presence of grid irregularity resulting from Chombo's block cartesian adaptive mesh requires special treatment of the charge assignment / force interpolation steps. We developed a correction method based on Green's functions which leads to a physically consistent method. Several test problems were developed to verify our technique.
	Michael Sekora, Princeton University Phillip Colella, Computational Research Division, LBNL, Lawrence Berkeley National Lab 05/27/07-08/18/07 Extremum-Preserving Limiters for the Piecewise Linear Method and Piecewise Parabolic Method The overarching project was to develop a Godunov-type method for solving multi-dimensional hyperbolic conservation laws that preserves fourth-order spatial accuracy. Such a method can be constructed by combining a technique for computing fourth-order face quadratures and the fourth-order spatial differencing of the unsplit Piecewise Parabolic Method. However, to ensure higher-order accuracy it was critical to reformulate van Leer and Parabolic Profile Limiters so that they did not reduce the problem to first-order accuracy at smooth extrema.
	Benjamin Smith, Harvard University Ernest Szeto, Computational Research Div [CRBD], Lawrence Berkeley National Lab 06/25/07-09/17/07 Automated Sorting of Large All Versus All BLAST Datasets Recent advances in rapid genome sequencing techniques have allowed the generation of terabytes worth of biological data which must be stored, processed, and distributed. Particularly important to the analysis of this data is the study of similarities in genome sequences via tools such as the Basic Local Alignment Search Tool (BLAST). Running “All versus Allâ€� BLAST searches has been made possible, even for very large datasets, via the use of supercomputers. However, the output of such a search is a large collection of ï¬�les each containing many BLAST matches. To be useful, an efï¬�cient method for sorting the output of the BLAST search by query and subject taxon, and then further sorting these results by score, must be found. A highly parallel, binary search tree based algorithm was tested here on ~475 GB of data, comprising the results of an “All versus Allâ€� BLAST search on 2788 taxons. Running on a cluster of 35 dual CPU nodes, the complete sort took just under 14 hours.
Alumni
2008
	Jenelle Bray, California Institute of Technology Teresa Head-Gordon, Physical Biosciences Division, Lawrence Berkeley National Lab Calculation of Side Chain Conformational Entropy and the Discrimination of Native Protein Structures from Decoy Sets I developed a monte carlo algorithm to calculate the conformational entropy of side chains by determining the number of non-clashing side chain conformations for a protein backbone. This is being used to help find the native protein state from a set of decoys.
2007
	Julianne Chung, Emory University Chao Yang, Computational Research Division, Lawrence Berkeley National Lab High Performance 3-D Image Reconstruction for Molecular Structure Determination The single particle reconstruction process from cryo-electron microscopy (cryo-EM) consists of taking a collection of 2-D projection images from various angular orientations and recovering a 3-D volume representation. Accurate volume reconstruction can provide important information on complex molecular structures and their assemblies. However, the reconstruction process can be computationally challenging for large-volume structures, due to massive data and memory requirements. Current parallel implementations of reconstruction algorithms are inadequate for computing large-volume macromolecule structures, even on today's state-of-the-art high performance supercomputers. We propose an MPI parallel implementation which allows the volume data to be distributed among processors of a parallel computer, thereby overcoming the current per-processor memory limitations. In addition, we propose using a Lanczos-based reconstruction algorithm for cryo-EM data and show that this algorithm computes better reconstructions in fewer iterations.
2006
	Christopher Carey, University of Wisconsin Phillip Colella, Computational Research Division, Lawrence Berkeley National Lab Modeling Ideal MHD collimation from differential rotation using an upwinding scheme with adaptive mesh refinement This project involved building a model of an astrophysical jet system using an existing magnetohydrodynamics (MHD) code built in the Chombo framework. Chombo is a framework for using upwinding methods for hyperbolic partial differential equations with adaptive mesh refinement. The model for the astrophysical jet system treats the accretion disk as a boundary condition, by applying a differentially rotating flow to fluid velocity on the bottom boundary. This flow winds up a small scale magnetic arcade which is set as the initial condition, and expands is to large length scales. This model will run with a computational domain with a length scale which is much larger than the characteristic length scale of the initial magnetic field. Thus, the boundary conditions on the outer boundaries will not have an influence on the evolution of the system. The adaptive mesh will allow for small scale structures in the solution fields to be resolved in this large domain.
	Kevin Kohlstedt, Northwestern University Teresa Head-Gordon, Physical Biosciences Division, Lawrence Berkeley National Lab Quaternary structure and stability of glycine mutated Amyloid Beta fibrils Amyloid beta (AB) fibril plaques have been recently studied due to their role in Alzheimers and Parkinson's disease. Although many recent structural studies have been done on the fibrils, still the arrangement of AB(1-40) monomers in the fibril remains a mystery. Using two quaternary structures proposed by Tycko, et al. for Wild Type AB(1-40) fibrils we studied the stability of the mutations in the two structures. A coarse grained model developed in the Teresa Head-Gordon was used in the dynamical simulations of the fibrils. The model is a four-bead group model, which groups the atoms in an amino acid into one bead. The flavor of the bead, which determines its interaction potential, is derived from its side chain properties. There are four flavors, strong hydrophobic, weak hydrophobic, neutral, and hydrophilic. Using this model we did simulation experiments using Langevin dynamics. We found the structure symmetric with the z-axis (axial to fibril) to be the more stable structure. We propose our model is able to capture the salient properties of the mutated fibril's structure and stability, which gives us insight into the behavior and morphology of the fibrils in vivo.
	Etay Ziv, Columbia University Adam Arkin, Physical Biosciences, Lawrence Berkeley National Lab Stochastic modeling of HIV Tat-transactivation The long-term goal of the project is to build a stochastic model of gene expression in the HIV LTR (Long Terminal Repeat) which includes various mechanisms of transcriptional control. HIV establishes a long-lived latent reservoir in infected CD4 resting cells, and this is thought to be the major mechanism by which HIV thwarts eradication in patients. It has been hypothesized that the stochastic expression of the TAT protein controls the viral life-cycle decision. Experimental collaborators have constructed strains containing the LTR promoter along with the Tat protein, tied to flourescent reporters. Using flow cytometer data from these constructs and various mutants, we seek to build a quantitative model of Tat expression.
2005
	Jasmine Foo, Brown University John Bell, Center for Computational Sciences and Engineering, Lawrence Berkeley National Lab Algorithm Refinement for the Stochastic Burgers' Equation This summer we designed and implemented a numerical method using adaptive algorithm refinement for Burgers' equation with a stochastic flux term. This hybrid method couples a particle simulation of an asymmetric exclusion process to a godunov-type finite difference solver for the stochasic PDE (SPDE). The asymmetric exclusion process is a system of random walker particles whose behavior in the hydrodynamic limit matches the solution to the SPDE. The hybrid method thus utilizes this particle model in some regions of the physical domain, and a continuum model elsewhere. The solver adaptively chooses to use the particle method in regions of high regional gradient. Using this hybrid solver, we studied the dynamics of the system by investigating properties such as the drift of the shock location over time and the effect of turning off the random component in the SPDE region.
	Amber Jackson, University of North Carolina - Chapel Hill John Bell, Computational Research Division, Lawrence Berkeley National Lab A Numerical Study of the Kelvin-Helmholtz Instability on Large Amplitude Internal Waves The project looked at large internal gravity waves in density stratified fluid. Adaptive Mesh Refinement Code (AMR) developed by LBNL was used to numerically simulate the experimental findings of a paper by Grue et al which presented the wave profiles, velocity profiles, wave propagation speeds, and instabilities associated with large internal solitary waves. Once satisfied that the numerics correctly captured the experiment, the code was also used to provide comparisons to new theoretical models purposed by Camassa and Choi. The final stage of the project involved looking specifically at Kelvin Helmholtz (KH) instabilities to characterize when and based on what parameters we should expect such instability to occur.
	Mala Radhakrishnan, Massachusetts Institute of Technology Adam Arkin, Departments of Bioengineering and Chemistry, Lawrence Berkeley National Lab Towards a Mechanistic Model of Agonist-Induced Calcium Signaling in Macrophage Cells Working with experimentalists in the Alliance for Cellular Signaling (AfCS) our goal is to construct a computational model that describes and predicts the time-dependent cytoplasmic calcium levels in cells as a function of external stimuli. The experimentalists generate large amount of time-dependent, dose-dependent, and knockdown-dependent calcium data, and we are using such data, as well as knowledge of the biological system, to create our model. In turn, our model allows us to suggest new experiments that can further refine the model. The cycle of experiment and model refinement is the hallmark of this project and will culminate in a model that captures the relevant effectors involved in Calcium signaling in the cell. This project has great utility; such a model, if accurate and quantitative enough, may someday help inform drug designers about the efficacy and the cellular-level impact of an agonist, thus saving time, energy, and experimental resources.
	William Triffo, Rice University Manfred Auer, Life Sciences, Lawrence Berkeley National Lab Tomography of molecular machines central to mechanotransduction in hair cells Hair cells are mechanically sensitive cells that transduce mechanical signals into electrical information through displacements of hair-like stereocilia at their apex; they are medically important in hearing and balance disorders. Electron tomography utilizes transmission electron microscopy (TEM) to generate 3D density maps with nanometer resolution, enabling us to resolve molecular complexes within their native cellular environment. This project focused on two structures related to mechanotransduction: the rootlet at the base of the stereocilium, and the lateral wall of the outer hair cell (OHC), which plays a pivotal role in mammalian hearing. Tomography was used to identify the 3D architecture and potential molecular composition of macromolecular machines, and to use this structural information to deduce mechanical function.
	Brandon Wood, Massachusetts Institute of Technology Joel Moore, Materials Science, Lawrence Berkeley National Lab Transfer-matrix approach to phonon defect scattering in three-dimensional carbon structures with thermoelectric applications The study was motivated by the possibility of using carbon nanotubes for direct thermal-to-electric energy conversion. Their theoretically high thermal conductivity and electrical tunability make them ideal candidates for thermoelectrics. In practice, however, defects in the nanotubes cause scattering of phonons (the primary thermal conduction mechanism) and inhibit their usefulness. The work I did involved using computational models to understand how randomly distributed defects (isotopic mass defects, in our prototypical example, although others are possible) affect the phonon dispersion spectrum of nanotubes. Having a better physical understanding of the problem could then lead to overcoming manufacturing barriers.
2004
	Benjamin Lewis, Massachusetts Institute of Technology Michael Eisen, Life Sciences, Lawrence Berkeley National Lab "Prediction of Regulatory Motifs Controlling the Expression and Processing of MicroRNA Genes in Drosophila" "Prediction of Regulatory Motifs Controlling the Expression and Processing of MicroRNA Ge By comparing genome sequences from multiple species, researchers may uncover functional regulatory elements that have been preserved in evolution. The genome sequences of related fruitfly species are an excellent resource for the identification and analysis of regulatory elements by multi-genome comparison. MicroRNA genes, a class of noncoding RNA genes, are an excellent subject for comparative genomics analyses of functional regulatory elements for several reasons: 1) microRNA genes are highly-conserved among divergent species 2) microRNA genes are small in size and may be easily-located in draft genome sequence 3) the expression of many microRNA genes is thought to be tightly-regulated in a cell-specific and developmental stage-specific manner. In this project, I have worked on the assembly and annotation of genome sequence data for 6 species of fruitfly. I have mapped all known microRNA genes in these genomes and I used comparative genomics methods to predict possible regulatory sequences involved in the expression of microRNA genes.
	Michael Wolf, University of Illinois at Urbana-Champaign Esmond Ng, National Energy Research Scientific Computing, Lawrence Berkeley National Lab Improving the Performance of the Scaled Matrix/Vector Multiplication with Vector Addition in Tau3P, an Electromagnetic Solver. At the Stanford Linear Accelerator Center, I developed a parallel 3-D distributed-memory time domain electromagnetic solver (Tau3P) that uses unstructured meshes to model large particle accelerator structures. This code has been successful in solving accelerator structures consisting of millions of elements. However, during the development of Tau3P, I found that it was very difficult to obtain good parallel efficiency when a large number of processors were used in an attempt to reduce the runtime sufficiently for running large problems. Some preliminary work has been done on trying to find more optimal mesh partitioning using Zoltan from Sandia National Laboratories in order to obtain better parallel efficiency. For my summer practicum, I focused on studying the communication patterns in Tau3P and trying different communication methods to reduce the communication overhead and increase parallel performance. In particular, I attempted to improve the parallel performance of the scaled matrix/vector multiplication with vector addition algorithm. I implemented over thirty different variations of this algorithm, exploring several different communication/computation orderings as well as many different modes of communication. I generated several different meshes so that I could examine the scalability of each algorithm as the problem size increases. I then ran the simulations on the IBM SP at NERSC. I found several communication schemes that were significantly better than the others, some surprisingly so.
2003
	Michael Barad, University of California, Davis Phillip Colella, Applied Numerical Algorithms Group, Lawrence Berkeley National Lab A Fourth Order Accurate Adaptive Mesh Refinement Method for Poisson’s Equation In this project we developed a fourth order accurate numerical method for solving Poisson’s equation, with adaptive mesh refinement (AMR) in 2 and 3 spatial dimensions, with either periodic, Neumann or Dirichlet boundary conditions. Our approach uses a conservative finite volume discretization combined with an efficient Multigrid elliptic solver. We use a cell-centered discretization, and using the divergence theorem, evaluate compact fourth order accurate fluxes at the faces of the cells.
	Michael Driscoll, Boston University Adam Arkin, Physical Biosciences Division, Lawrence Berkeley National Lab Characterization of a Pulse-Generating Gene Circuit Using Quantitative Real-Time PCR Dr. Adam Arkin, a Faculty Scientist at the Lawrence Berkeley National Laboratories, is presently engaged in a project to forward engineer genetic regulatory circuits in E.Coli. Cells are multistable systems which can reliably switch between states, for example during development or cell division, based on environmental signals. This capacity for switching states and the ability to maintain a given state is a product of a cell's complex genetic regulatory circuitry. I collaborated with a member of Dr. Arkin's group, Michael Cantor, in building a pulse-generating genetic circuit in E.Coli. This gene circuit consists of four genes coupled with promoter sequences arranged on a plasmid vector. These four genes regulate one another in such a way as to form a simple pulse-generating circuit. This circuit is induced by the addition of the sugar arabinose, and responds by transiently expressing a green fluorescent protein. By providing a means of introducing a transient pulse of a gene product into a system, the pulse generating circuit represents an important tool for the study of gene networks.
	Kristen Grauman, Massachusetts Institute of Technology Bahram Parvin, Computing Sciences, Imaging and Informatics Group, Lawrence Berkeley National Lab Automatic segmentation and labeling of images of different cell types The goal of this project was to use image processing and computer vision techniques to analyze images of breast tissue in order to segment and label the different cell types present in a given image. The eventual goal is to collect a large volume of data in this way, and then potentially establish correlations or patterns in the data that might explain the link between the tissue's biological condition and its appearance.
	Yan Karklin, Carnegie Mellon University Stephen Holbrook, Physical Biosciences Division, Lawrence Berkeley N, Lawrence Berkeley National Lab Learning RNA Secondary Structure using Marginalized Kernels on Graphs The goal of this project was to apply several new techniques in bioinformatics and machine learning to finding non-coding RNAs in genomes. Recent work has identified an increasing number of small RNA molecules that do not code for proteins but are nevertheless transcribed from DNA. These "non-coding" RNAs have many different funtional roles, and the facilitation of their discovery by computational analysis of genome sequences is a useful undertaking. There exist large databases of sequenced, functional family-annotated RNA. Using the primary sequence, it is possible to predict the secondary structure (base-pairing and folding) fairly reliably, and the shape of the folded non-coding RNAs may indicate the functional role of the molecules. This project attempted to build a classifier to learn the typical shapes of secondary structures of RNA molecules. RNAs were represented as graphs, and (the recently developed) kernels between labeled graphs were used in the SVM classifier. Preliminary results suggest that this approach provides a decent alternative to sequence-based methods for finding non-coding RNAs.
	Julian Mintseris, Boston University Michael Eisen, Life Sciences, Lawrence Berkeley National Lab Inference of Protein-DNA Binding Specificity From Structure The goal of the project is to take advantage of the increasing amount of structural data available to try to improve our understanding of protein-DNA recognition and regulation. Specifically, we are interested in inferring protein-DNA binding profiles from structure databases to enable better prediction of cis-regulatory motifs in genomes.
	Gregory Novak, University of California, Santa Cruz Martin J. White, Physics, Lawrence Berkeley National Lab Numerical Simulations of the Lyman Alpha Forest The Lyman Alpha Forest (LAF) is a dense set of absorption lines seen in the spectra of distant quasars due to clouds of neutral hydrogen along the line of sight. The detailed structure of the LAF gives information about both the spectrum and the amplitude of density fluctuations in the early universe that gave rise to all present-day structure in the universe. The goal of the project was to produce a code to numerically simulate the evolution of intergalactic gas from the big bang to a time when the universe was 3-4 times smaller than its present size. The state of this gas determines the statistical properties of the LAF that would be seen by an observer who "lived in" the simulation. By comparing the observed properties of the LAF to the properties of the simulated LAF, it is possible to answer a number of questions about the cosmological parameters of the universe. For example, it has been shown (Croft 1998) that under a number of simplifying assumptions, it is possible to use simple prescription for the state of intergalactic gas in the early universe (rather than full fledged simulation) to to measure the amplitude of the initial density fluctuations in the universe to an accuracy of about ten percent. However, one of the simplifying assumptions in this analysis is that the ultraviolet background light in the early universe is homogeneous. Direct simulation can quantify the effect of inhomogeneities in the ultraviolet background, which can be expected to degrade the accuracy of the measurement. Croft, Weinberg, Katz and Hernquist, Astrophysical Journal 495:44 (1998).
	Joshua Waterfall, Cornell University Daniel Rokhsar, Physical Biosciences Division/JGI, Lawrence Berkeley National Lab May 21 - August 21 Polymorphisms in Ciona intestinalis Analyzed shotgun genome sequence from several Ciona intestinalis individuals for polymorphisms, genetic differences between members of the same species. Studied correlations with and evidence for evolutionary selection on different features of the genome such as coding regions, intergenic regions, and regulatory sequences. Also developed tools to analyze DNA methylation in several of the genomes sequenced at the JGI, including Ciona intesinalis, Fugu rubripes and Human chromosome 17.
2002
	Ahna Girshick, University of California, Berkeley Anat Biegon, Center for Nuclear Medicine & Functional Imaging, Lawrence Berkeley National Lab 5/27/02-8/15/02 Understanding the brain is one of the most challenging scientific problems facing us today. The advent of medical imaging techniques such as CT, PET, SPECT, and MR has enabled scientists with invaluable non-invasive tools for viewing the brain’s 3D anatomical structure. More recently, imaging has moved beyond anatomy to studies of brain function. Functional magnetic resonance imaging (fMRI) records brain activity over time which can then be used to correlate anatomical structures with specific behavioral and cognitive processes. Such studies require processing and interpretation of time series of high-resolution 3D image sets which could not be approached without high performance computing technology. I worked at the Center for Functional Imaging with Dr. Anat Biegon on a study to test the hypothesis that hormones influence recovery from traumatic brain injury. One objective of this project is to determine whether differences in brain structure and functional organization can explain sex and age differences in outcome from traumatic brain injury. Structural MRI and multifunctional (language, vision, audition, sensory and motor) fMRI activation studies were run on groups of young and older men and women. Volumes of activation to the specific stimuli were computed and normalized by gray matter volume and compared across groups using a two-way ANOVA (by sex and age). The long-term goal is to extend this technique to patients a year or more after a traumatic brain injury. Dr. Biegon hypothesizes that good recovery will be associated with functional reorganization, and that the efficiency and pattern of reorganization may be influenced by gonadal hormone status. The Center for Functional Imaging uses an impressive cluster of UNIX workstations for computational support, including several multi-processor SGIs. In collaboration with Dr. Greg Klein, I used these facilities to do an image analysis on the time series of 3D fMRI data.
	Mary Ann Leung, University of Washington Dr Andrew Canning, Scientific Computing, Lawrence Berkeley National Lab July 1 - September 20, 2002 Investigation of quantum well states in Copper-Cobalt thin films. Project Description: We investigaged the properties of quantum well states in Copper/Cobalt thin fim systems using density functional theory. The Copper/Cobalt quantum well states are believed to be responsible for the "Giant Magneto-Resistance", or GMR effect that is responsible for the development of super dense, high-capacity hard disk drives. We investigated the properties of the quantum well states found in the Copper thin films by running simulations, using Paratec, a code that implements density functional theory and runs on parallel processign super computers. We inserted a Nickel atom at various locations in the thin film to determine effects on the quantum well states by the Nickel atom.
2001
	Benjamin Keen, University of Michigan Dr. Phil Colella, Applied Numerical Algorithms Research Group, Lawrence Berkeley National Lab 5/25/01-8/25/01 Implementing an embedded boundary algorithm for gas dymamics in EBChombo. I implemented an embedded reflecting boundary algorithm for hyperbolic conservation laws (Modiano and Colella 2000). This is useful because it is a more general implementation of the algorithm than was done in the paper, and because it is one of the first applications using the EBChombo embedded boundary C++ application framework currently under development at ANAG.
	Heather Netzloff, Iowa State University Teresa Head-Gordon, Physical Biosciences and Life Science, Lawrence Berkeley National Lab 5/28/01-8/17/01 Parallelization of the Ewald Summation Method in Molecular Dynamics My project focused on parallelizing various methods to account for long-range forces in molecular dynamic (MD) simulations. The evaluation of forces is the major bottleneck to any MD simulation. Since the basic minimum image convention cutoff scheme does not accurately account for long-range interactions, new methods have been developed. These include the Ewald sum method in which the potential energy calculation is divided into a real-space sum and a reciprocal space sum. Since we desire to accurately simulation events such as protein folding in the condensed phase, the size of our system requires the use of parallel, efficient algorithms. There are several methods available to parallelize a MD code with various scalings; the focus of my research was to implement and benchmark these methods for future reference in protein simulations. The first two methods described divide the work between real and reciprocal space. In the atom decomposition method, each processor is given a static number of molecules; each processor computes the forces and new positions for its local molecules and then must share new positions with the rest of the processors. The force decomposition method involves assigning each process a portion of the force matrix. Each processor again contains a static number of local molecules, but will only compute a portion of the force matrix. The pertinent pieces of the force matrix are then shared among a smaller subset of processors to update total forces on local molecules. The particle mesh Ewald method puts emphasis on the reciprocal space sum; it is evaluated using fast Fourier transform with convolutions on a grid where charges are interpolated to the grid points. The fast multipole method, theoretical an O(N) method, calculates all forces in real space. The first two methods were parallelized during my summer practicum and research into the third was started. Reasonab
	Catherine Norman, Northwestern University Ann Almgren, Center for Computational Sciences and Engineering, Lawrence Berkeley National Lab 6/11/01-8/31/01 Modeling Multiphase Fluid Flow with Level Set Methods I worked with a variable density Navier Stokes solver which the Center for Computational Sciences and Engineering at LBL has written and used to model a variety of fluids problems. As part of ongoing efforts to improve and augment this model, I added code to track interfaces between fluids using level set methods.
	Catherine Quist, Cornell University Dr. Stephen R. Holbrook, Physical Biosciences Division, Lawrence Berkeley National Lab 5/21/2001 - 8/24/2001 RNA Gene Finding In Eukaryote Identifying the "coding" regions of the human genome is one of the chief aims of the human genome project, or of any genome project for that matter. While this is a difficult problem, it is by no means impossible, especially if the search for coding regions is restricted to protein genes, i.e. stretches of DNA which are transcribed into mRNAs and then translated into proteins. Since all regions of DNA that code for a protein are flanked on one side by a start codon (three base pairs which signal to the ribosome to use a methionine to initiate construction of an amino acid chain) and on the other side by a stop codon (three base pairs which signal to the ribosome to release the mRNA and thereby halt translation), they may be relatively easily identified by a computer program using a hidden markov model. If the search for "coding" regions is restricted to RNA coding regions instead of protein coding regions the problem of gene finding becomes much harder by comparison. While RNA genes are still transcribed, they are not translated and thus lack start and stop codons. A computer program which finds potential RNA genes cannot do so by searching for these markers. It must instead search for adjacent trascription regulatory regions and conserved structural motifs. Due to the complexities and subtleties of the patterns associated with these markers, along with our lack of a deeper understanding of either the protein-DNA complexes that initiate transcription or RNA folding, recognizing them is a very hard machine learning problem. Dr. Stephen R. Holbrook at LBNL has written a program, which uses neural networks to do RNA gene finding in prokaryotes. I spent the summer modifying this program to do RNA gene finding in Yeast, the simplest Eukaryotic organism.
2000
	Rellen Hardtke, University of Wisconsin Stewart Loken and George Smoot, , Lawrence Berkeley National Lab 6/1/2000 - 9/1/2000 Project 1 (A) "Archiving the 1999 AMANDA Data Set" Project 2 (B) "Enlarging the Gamma-Ray Burst Sample for AMANDA" (A) Each year data collected by the Antarctic Muon and Neutrino Detector Array (AMANDA)is copied to DLT tapes at the South Pole experimental site. This set of -70 DLT tapes contains more than 1 terabyte of data and is hand-carried out of Antartica when the site becomes accessible in November. Once these tapes reach LBNL, they must be first be uploaded to the National Energy Research Scientific Computing Center (NERSC) mass storage facility before the data can be filtered and utilized by scientists. Quality checks and monitoring must be undertaken, as well as annual improvements and updates made in the archiving scrips. (B) One of AMANDA's scienfic projects is the search for neutrinos from gamma-ray bursts (GRBs). These extremely energetic phenomena are little understood and the detection of neutrinos from these events would be a major discovery. Prior to this summer, only 78 GRBs had been studied for coincident neutrinos. My goal was to increase the number of GRBs that AMANDA could examine by finding a new source of detected GRBs and extracting the necessary data from AMANDA archives at LBNL.
1999
	William Marganski, Boston University Jamie Butler, , Lawrence Berkeley National Lab 5/21/1999 - 8/13/1999 Measuring the Extensional Elasticity of the Red Blood Cell Using Micropipette Aspiration The extensional elasticity of the red blood cell represents the major force of recovery after large cell deformations. The source of the extensional elasticity is the cytoskeleton underneath the cell membrane. This protein scaffolding consists of a spectrin network that is interconnected via short actin filaments and protein 4.1. The elasticity of the cytoskeletal network is dependent upon its linkage to the lipid membrane via band 3 and ankyrin and its association with other transmembrane proteins such as glycophorin A. The elasticity of the red cell's protein scaffolding can be quantitated by mechanical aspiration into a suction pipette. An elastic modulus for the cytoskeleton of the red blood cell can be calculated by measuring the aspiration length of the cell within the micropipette as the suction pressure is increased.
1998
	J. Dean Brederson, University of Utah Dr. Edward Bethel, Visualization Group, Lawrence Berkeley National Lab 6/15/1998 - 9/2/1998 Implementation Issues in Haptic Visualization The goal of this research is to solve several of the problems inherent in integrating haptic interfaces with scientific visualization environments. In particular, a PHANTOM haptic interface was used as the device of interaction. Two specific problems that were the goal of the practicum were to develop a closed-loop calibration scheme for the device and a set of low-level device drivers to enable accurate haptic rendering within a calibrated workspace at high servo rates.
	Eugene Ingerman, University of California, Berkeley Dr. Alexandre Chorin, , Lawrence Berkeley National Lab 5/25/1998 - 8/24/1998 Numerical Experiments with Optimal Predictions Method My project consisted of studying the applicability of the optimal predictions method to several types of the differential equations.
1997
	Brandoch Calef, University of California, Berkeley Dr. Malcolm Howells, AFRD, Lawrence Berkeley National Lab 5/20/1997-8/15/1997 Image Recovery Using Multiple Holograms Two or more holograms are made of an object at different distances. The holograms are digitized and loaded into a computer. The problem then is to reconstruct an image of the object. Iterative techniques were devised to achieve this.
	Marc Serre, University of North Carolina Dr. Garrison Sposito, Earth Sciences Division, Lawrence Berkeley National Lab 5/5/1997 - 7/25/1997 Using the Space Transformations to solve the Three Dimensional Flow Equation New formulations of the space transformations have been derived and implemented for bounded flow domains. The new formulations are more accurate than previous methods. Additionally this new implementation was tested on the T3E supercomputer.
1995
	John Guidi, University of Maryland Dr. Manfred Zorn, Information and Computing Sciences, Lawrence Berkeley National Lab 5/30/1995 - 8/25/1995 Integration of physical and genetic genome maps The delineation of the ordering of chromosomal loci is an important objective of biomedical research. A variety of experimental techniques exist that provide order information at different levels of resolution, using various coordinate systems. This project focuses on the issues involved in integrating disparate ordering information, taking into consideration the uncertainties and ambiguities that are present.
	Philip Weeber, University of North Carolina Dr. T.N. Narasimhan, Earth Sciences Division, Lawrence Berkeley National Lab 8/15/1995 - 8/18/1995 Slug Tests Under Saturated/Unsaturated Flow: A Richard's Equation Perspective Applying computer model to physical problem of groundwater flow through porous media.
1993
	Edwin Blosch, University of Florida Dr. James Sethian, Physics Division, Lawrence Berkeley National Lab 9/1/1993 - 8/31/1994 Parallel Computation using OVERFLOW: Overlapping Grid Navier-Stokes Flow Solver An overlapping grid scheme based on the Chimera approach has been developed by NAS for solving the N-S eqn's on the iPSC/860 MIMD computer. The code was benchmarked on three model flow problems: (1) supersonic flow over a wedge, (2) transonic flow over a wing at angle-of-attack, and (3) obliques shock wave/turbulent boundary layer interaction with bleed to prevent separation. Parallel computing issues have also been investigated, includiing the effect of domain decomposition of parallel efficiency.
	Jack Lemmon, Georgia Institute of Technology Dr. Thomas Budinger, Center for Functional Imaging, Lawrence Berkeley National Lab 6/7/1993 - 7/15/1993 Examination of Image Reconstruction from Transmission Data Examined the reconstruction of medical images from position emissions using existing algorithms.

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