VictorJuiz/thesis huggingface dataset:
Novel approaches to the visualization of cell specific gene expression patterns [electronic resource]

The fate of a cell is largely determined by the unique patterns of gene expression found within it. Complex biological machinery exists within each cell to manipulate chromatin state, and ultimately control gene expression. Developmental processes such as cellular differentiation require very specific chemical signals and environmental conditions. These serve as triggers to put the chromatin modification schemes that produce the resultant patterns of differential gene expression into action, leading to the formation of the cell type of interest. My thesis work is an in depth study of the link between chromatin modification, gene expression, and the unique genetic signatures that characterize distinct cells on unicellular and multi-cellular levels. On the multi-cellular level, I have examined histone modification patterns for their effects on gene activation and repression during human embryonic stem cell differentiation. On the unicellular level, I have worked with a variety of cell types to ascertain the degree of individuality that exists between single members of relatively homogenous cell groups while simultaneously looking for housekeeping gene expression signatures that can be used to classify each cell type into a unique group. To further elucidate the patterns of gene expression found within cell groups and the single cells that comprise them, I have worked to develop new computational methods that produce visual aids to elucidate gene expression signatures of single cells and cell groups.

Keywords: Bioengineering.
Advisor: Baker Julie (Professor of genetics) primary advisor. Thesis advisor
Altman Russ advisor. Thesis advisor
Deisseroth Karl advisor. Thesis advisor
Novel genetic elements and features of the caulobacter crescentus system [electronic resource]

In the last decade remarkable technologies, such as high-density tiling arrays and high-throughput DNA sequencing have enabled whole-genome studies at an unprecedented scale and resolution. In this work I describe how we used these technologies to map novel genetic elements as well as regulatory features of the bacterium Caulobacter crescentus, a model species used for understanding the prokaryotic cell-cycle. I describe a dynamic programming algorithm I used to determine the location of 27 novel small RNA transcripts (sRNAs), several novel antisense RNA transcripts, as well as the accurate mapping of mRNA transcripts. Many of these predictions were validated biochemically. In addition, I describe how we coupled high-throughput transposon mutagenesis with statistical analysis to map all the essential genetic elements in the Caulobacter crescentus genome to 8 base-pair accuracy. We found that 480 out of the 3960 genes contained in Caulobacter's genome are essential for cell viability, as well as 3 out of the 27 novel sRNA that we had identified. Interestingly, there are 90 essential small intergenic DNA segments of unknown function. Finally, I describe the operon organization of Caulobacter's genome.

Keywords: Electrical Engineering
Advisor: McAdams Harley primary advisor. Thesis advisor
Dill David L. advisor. Thesis advisor
Osgood Brad advisor. Thesis advisor
Shapiro Lucy advisor. Thesis advisor
Numerical approaches to theory of spectroscopy in correlated materials [electronic resource]

Strongly correlated systems exhibit novel phenomena such as superconductivity and magnetism that arise from the interplay between many intertwined degrees of freedom. In this dissertation I discuss my work using state-of-the-art exact diagonalization simulations in attempts to understand the physics of correlated materials via their response to various experimental probes. I first discuss simulating x-ray absorption spectra to extract crucial information regarding correlation effects in iron-based superconductors and the pressure-induced phase transitions in hematite. I then discuss modeling resonant inelastic x-ray scattering spectra of the cuprate superconductors and studying the orbital characters of the excitation profiles. Following the discussion of photon-based spectroscopies, I then shift the focus to magnetic properties of iron-based superconductors. I will discuss a possible orbital ordering scenario in connection with the orthorhombic anisotropies observed in neutron scattering, transport, and other spectroscopic experiments performed on these materials. At the end of the dissertation, I examine the role of magnetic frustration and demonstrate how the response of antiferromagnets to non-magnetic impurities and magnetic Raman scattering can reveal the degree of frustration and help narrow the possible models for the iron-pnictide materials.

Keywords: Physics
Advisor: Devereaux Thomas Peter
Kivelson Steven advisor. Thesis advisor
Raghu Srinivas
Offloading Critical Security Operations to the GPU

General computing with Graphics Processing Units (GPUs) has taken off the last few years because of their unique ability to perform parallel calculations very efficiently.
More developers have started to take advantage of this processor to improve software performance. Similarly, security developers have considered using the GPU to offload calculations as a way to improve the speed and robustness of security software. In this thesis, I outline reasons why this process might not necessarily be secure and provide experiments I have performed to find security flaws in GPU offloading.

Keywords: Computer Science.
Graphics processing units
Data encryption > Computer science
Thesis
Advisor: Boneh Daniel
On a free boundary problem for embedded minimal surfaces and instability theorems for manifolds with positive isotropic curvature [electronic resource]

In this thesis, we describe a min-max construction of embedded minimal surfaces satisfying the free boundary condition in any compact 3-manifolds with boundary. We also prove the instability of minimal surfaces of certain conformal type in 4- manifolds with positive isotropic curvature. Given a compact 3-manifold M with boundary [d̳]M, consider the problem of find- ing an embedded minimal surface [Sigma] which meets [d̳]M orthogonally along [d̳][Sigma]. These surfaces are critical points to the area functional with respect to variations preserving [delta]M. We will use a min-max construction to construct such a free boundary solution and prove the regularity of such solution up to the free boundary. An interesting point is that no convexity assumption on [d̳]M is required. We also discuss some geometric properties, genus bounds for example, for these free boundary solutions. Just as positive sectional curvature tends to make geodesics unstable, positive isotropic curvature tends to make minimal surfaces unstable. In the second part of this thesis, we prove a similar instability result in dimension 4. Given a compact 4- manifold M with positive isotropic curvature, we show that any complete immersed minimal surface [Sigma] in M which is uniformly conformally equivalent to the complex plane is unstable. The same conclusion holds in higher dimensions as well if we assume that the manifold has uniformly positive complex sectional curvature. The proof uses the H ̈ormander's weighted L^2 method and the stability inequality to derive a contradiction.

Keywords: Mathematics
Advisor: Schoen Richard (Richard M.) primary advisor. Thesis advisor
Simon L. (Leon)
White Brian
On asymptotically optimal source coding and simulation of stationary sources [electronic resource]

Source coding or lossy data compression has been extensively studied ever since Shan- non formally described the problem more than half of a century ago. Yet source coding schemes approaching the theoretical Shannon limit even on simple stationary sources such as IID Gaussian or IID uniform sources remain elusive. In this dissertation, both source coding and the related rate-constrained simulation problem are studied. Four necessary conditions for asymptotically optimal sliding-block or stationary codes for source coding and rate-constrained simulation are derived. The first two necessary conditions are proved for stationary ergodic sources while the remaining two necessary conditions are proved for IID sources. A new code design algorithm which attempts to satisfy all four necessary conditions is presented. The code structure has intuitive similarities to classic random coding arguments as well as to "fake process" methods and alphabet-constrained methods. Experimental results show that the new coding design algorithm provides comparable or superior performance with respect to previously published methods on common IID and autoregressive examples, often by significant margins. In many cases, such as IID Gaussian, IID uniform and discrete IID binary sources, the performance approaches the theoretical Shannon limit.

Keywords: Electrical Engineering
Advisor: Gray Robert M.
Gill John advisor. Thesis advisor
Weissman Tsachy advisor. Thesis advisor
On harmonic maps into conic surfaces [electronic resource]

We prove the existence and uniqueness of harmonic maps in degree one homotopy classes of closed, orientable surfaces of positive genus, where the target has non-positive gauss curvature and conic points with cone angles less than

Keywords: Mathematics
Advisor: Mazzeo Rafe primary advisor. Thesis advisor
Schoen Richard (Richard M.) advisor. Thesis advisor
Vasy András advisor. Thesis advisor
On latent systemic effects in multiple hypotheses [electronic resource]

This dissertation deals with two closely related topics of latent systemic effect in multiple hypothesis testing in addition to supplying an overview of the growing literature in the field. The first part aims at searching for associations with a primary variable among a great many candidate variables in high throughput settings. High throughput hypothesis testing can be made difficult by the presence of systemic effects and other latent variables. Dependencies can change the relative ordering of significance levels among hypotheses. We propose a two stage analysis to counter the effects of latent variables on the ranking of hypotheses. Our method, called LEAPP, statistically isolates the latent variables from the primary one. In simulations it gives better ordering of hypotheses than competing methods such as SVA and EIGENSTRAT. For an illustration, we turn to data from the AGEMAP study relating gene expression to age for 16 tissues in the mouse. LEAPP generates rankings with greater consistency across tissues than the rankings attained by the other methods. The second part studies the detection of DNA copy number variation (CNV) across samples. Experimental artifacts, such as local trends, if not carefully removed, may be misconstrued as significant recurrent regions. We develop an alternating algorithm to adjust the effects of latent variables on the detection of recurring CNVs. Our method, called CNVlatent, improves accuracy in detecting CNVs for simulated data compared to methods without adjustments for latent effects. We resort to two data sets for illustration. One is from the chromosome 9p region in 44 pediatric leukemia samples and the other is from a region on cytoband 11 on the q-arm of chromosome 22. CNVlatent successfully detects visible copy number changes and adjusts for the latent effects. There are many studies regarding segmentation of CNVs, but incorporating copy number information into association tests remains an open problem for lack of accuracy of copy number genotyping. We proposed a statistical framework for genotyping CNVs on a detected genomic region encompassing the putative CNVs in the analysis of both inherited and somatic copy number variants. To pool information across SNPs, we take into account the different response rates and noise properties of each SNP. We carry out the model calibration with an Expectation-Maximization (EM) based algorithm. Our method achieves higher estimation precision in synthetic data and generate estimators with greater consistency across a data set with replicate samples than existing methods such as CNVtools.

Keywords: Statistics
Advisor: Owen Art B. primary advisor. Thesis advisor
Zhang Nancy R. (Nancy Ruonan) primary advisor. Thesis advisor
Efron Bradley advisor. Thesis advisor
Wong Wing Hung advisor. Thesis advisor
On redemption, the value of putting bad things to good use [electronic resource]

This dissertation offers a theory of a solution to the problem of lost meaning in life due to regrettable, past events. Each of us wishes for a meaningful life, but each of us, too, is vulnerable to threats to the meaning in life. The dissertation argues that a phenomenon called redemption can restore lost meaningfulness, and increase the value of our lives, overall. The first step in the argument is to demonstrate the need for a new model of redemption. The next step is to argue that redemption is a matter of transforming the meaning of events in our lives from bad to good in a thick, eudaimonistic sense related to a person's well-being. Finally, I show that this transformation not only increases a person's well-being but, more importantly, changes the relationship a person has with his past; By satisfying conditions for meaningfulness—a special value a life can have, distinct from its moral goodness or happiness—redemption renders the past more meaningful that it would have otherwise been. Because of this, redemption can solve the problem articulated in the beginning of the dissertation—the problem of lost meaning in life due to bad, past events.

Keywords: Philosophy
Advisor: Anderson R. Lanier primary advisor. Thesis advisor
Hills David James
Schapiro Tamar advisor. Thesis advisor
Wood Allen W. advisor. Thesis advisor
Open trade, closed borders [electronic resource] : immigration policy in the era of globalization

This thesis argues that immigration policy cannot be studied in the absence of trade and capital policy. Trade is a substitute for immigration for both policymakers and firms. Opening trade forces firms to become more productive, move overseas, or close their doors; all three choices reduce firms' incentives to push for open immigration and allows policymakers to move immigration policy closer to the ideal policy of the rest of their constituents by restricting immigration. Opening capital reinforces this effect by increasing the probability that firms will move overseas in response to trade openness instead of remaining at home. The thesis tests this theory on two new datasets, one on the immigration policy of 19 states from the late 18th century through the early 21st century and one on the voting behavior of US Senators on immigration from 1865-2008. In both datasets, there is a powerful, robust and enduring relationship between trade and immigration. Trade openness leads to greater immigration restrictions and this relationship is made stronger when we examine capital openness as well.

Keywords: Political Science.
Advisor: Goldstein Judith primary advisor. Thesis advisor
Laitin David D. advisor. Thesis advisor
Rivers Douglas
Tomz Michael advisor. Thesis advisor
Optimization techniques for segmenting 3D shapes [electronic resource]

With increasing amounts of data describing 3d shapes, geometry processing is becoming extremely important in fields ranging from computer graphics to robotics to medicine to computational biology. A fundamental task in geometry processing is to segment shapes into meaningful parts. Segmentation assists global parameterization, compression, animation and more. Moreover, it is crucial to shape understanding and semantics based object representations, which rely on feature extraction and structure extraction from 3d meshes that represent these objects and shapes. This thesis aims to advance shape segmentation techniques in three directions: joint segmentation of a collection of shapes, segmentation of repeated elements on curved surfaces, and vector field based segmentation. First, we present an approach to segmenting shapes in a heterogenous shape database. By considering multiple shapes in concert, our approach is able to identify meaningful parts despite the lack of strong geometric cues on a particular shape. Likewise, the approach is able to identify coherent single parts even when the geometry of the individual shape suggests the presence of multiple segments. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. Near-regular structures are common in man-made and natural objects. The second approach targets at segmenting the repeating elements of a near-regular structure on a curved surface. The approach proceeds in two steps. In the first step, it computes a near-regular mesh which represents the skeleton of the underlying near-regular structure. We present a sparse integer programming formulation to this problem whose linearized program is both tight and can be efficiently solved. In the second step, the approach segments the repeating elements through consistent region growing, starting at vertices of the near-regular mesh. Finally, we introduce vector-field based shape segmentation, which builds on the dual relationship between generalized Killing vector fields and segmentations. This approach allows us to control segmentations by designing appropriate Killing vector fields. It also features a low dimensional design space and interactive vector field editing. We show the application of this approach in interactive macro-patch segmentation for designing geodesic patterns.

Advisor: Guibas Leonidas J. primary advisor. Thesis advisor
Carlsson G. (Gunnar)
Koltun Vladlen
Optimization under uncertainty [electronic resource] : bounding the correlation gap

Modern decision models increasingly involve parameters that are unknown or uncertain. Uncertainty is typically modeled by probability distribution over possible realizations of some random parameters. In presence of high dimensional multivariate random variables, estimating the joint probability distributions is difficult, and optimization models are often simplified by assuming that the random variables are independent. Although popular, the effect of this heuristic on the solution quality was little understood. This thesis centers around the following question: "How much can the expected cost increase if the random variables are arbitrarily correlated?" We introduce a new concept of Correlation Gap to quantify this increase. For given marginal distributions, Correlation Gap compares the expected value of a function on the worst case (expectation maximizing) joint distribution to its expected value on the independent (product) distribution. Correlation gap captures the "Price of Correlations" in stochastic optimization -- using a distributionally robust stochastic programming model, we show that a small correlation gap implies that the efficient heuristic of assuming independence is actually robust against any adversarial correlations, while a large correlation gap suggests that it is important to invest more in data collection and learning correlations. Apart from decision making under uncertainty, we show that our upper bounds on correlation gap are also useful for solving many deterministic optimization problems like welfare maximization, k-dimensional matching and transportation problems, for which it captures the performance of randomized algorithmic techniques like independent random selection and independent randomized rounding. Our main technical results include upper and lower bounds on correlation gap based on the properties of the cost function. We demonstrate that monotonicity and submodularity of function implies a small correlation gap. Further, we employ techniques of cross-monotonic cost-sharing schemes from game theory in a novel manner to provide a characterization of non-submodularity functions with small correlation gap. Results include small constant bounds for cost functions resulting from many popular applications such as stochastic facility location, Steiner tree network design, minimum spanning tree, minimum makespan scheduling, single-source rent-or-buy network design etc. Notably, we show that for many interesting functions, correlation gap is bounded irrespective of the dimension of the problem or type of marginal distributions. Additionally, we demonstrate the tightness of our characterization, that is, small correlation gap of a function implies existence of an "approximate" crossmonotonic cost-sharing scheme. This observation could also be useful for enhancing the understanding of such schemes, and may be of independent interest.

Advisor: Roughgarden Tim primary advisor. Thesis advisor
Ye Yinyu primary advisor. Thesis advisor
Goel Ashish advisor. Thesis advisor
Saberi Amin advisor. Thesis advisor
Optogenetic reverse-engineering of brain sleep/wake circuitry [electronic resource]

The neural control of sleep and wakefulness depends upon a complex and partially defined balance between subcortical excitatory and inhibitory populations in the brain. Wake-active neurons include hypocretin (Hcrt)-containing neurons in the lateral hypothalamus and noradrenergic neurons that make up the brainstem locus coeruleus (LC). Experimentally determining a causal role for these neurons in promoting and maintaining wakefulness has remained elusive using traditional pharmacological and electrical techniques due to their small size, unique morphology, and proximity to heterogeneous neuronal and non-neuronal cell types. The recent development of optogenetic technology provides a toolkit of genetically-encodable, millisecond timescale, stimulation and inhibition probes that can be targeted to specific cell types with no toxicity to the cells under investigation. This dissertation discusses the application of optogenetic tools to questions about sleep/wake circuitry and uses these tools to study Hcrt and LC neurons, both individually and in combination.

Advisor: Lecea Luis de primary advisor. Thesis advisor
Deisseroth Karl advisor. Thesis advisor
Huguenard John advisor. Thesis advisor
Mignot Emmanuel