Plis S.M.,The Mind Research Network |
Sui J.,The Mind Research Network |
Sui J.,CAS Institute of Automation |
Lane T.,University of New Mexico |
And 11 more authors.
NeuroImage | Year: 2014
Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors ("network clusters"). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pairwise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important. © 2013 Elsevier Inc.
Anderson C.L.,University of Wisconsin - Madison |
Anderson C.L.,Wisconsin Institutes for Discovery |
Kuzmicki C.E.,University of Wisconsin - Madison |
Childs R.R.,University of Wisconsin - Madison |
And 3 more authors.
Nature Communications | Year: 2014
It has been suggested that deficient protein trafficking to the cell membrane is the dominant mechanism associated with type 2 Long QT syndrome (LQT2) caused by Kv11.1 potassium channel missense mutations, and that for many mutations the trafficking defect can be corrected pharmacologically. However, this inference was based on expression of a small number of Kv11.1 mutations. We performed a comprehensive analysis of 167 LQT2-linked missense mutations in four Kv11.1 structural domains and found that deficient protein trafficking is the dominant mechanism for all domains except for the distal carboxy-terminus. Also, most pore mutations - in contrast to intracellular domain mutations - were found to have severe dominant-negative effects when co-expressed with wild-type subunits. Finally, pharmacological correction of the trafficking defect in homomeric mutant channels was possible for mutations within all structural domains. However, pharmacological correction is dramatically improved for pore mutants when co-expressed with wild-type subunits to form heteromeric channels. © 2014 Macmillan Publishers Limited. All rights reserved.
Tang G.,Colorado School of Mines |
Shah P.,Wisconsin Institutes for Discovery |
Bhaskar B.N.,University of Wisconsin - Madison |
Recht B.,University of California at Berkeley
Conference Record - Asilomar Conference on Signals, Systems and Computers | Year: 2015
Line spectral estimation is a classical signal processing problem that finds numerous applications in array signal processing and speech analysis. We propose a robust approach for line spectral estimation based on atomic norm minimization that is able to recover the spectrum exactly even when the observations are corrupted by arbitrary but sparse outliers. The resulting optimization problem is reformulated as a semidefinite program. Our work extends previous work on robust uncertainty principles by allowing the frequencies to assume values in a continuum rather than a discrete set. © 2014 IEEE.
Salick M.R.,Wisconsin Institutes for Discovery |
Salick M.R.,University of Wisconsin - Madison |
Napiwocki B.N.,Wisconsin Institutes for Discovery |
Napiwocki B.N.,University of Wisconsin - Madison |
And 12 more authors.
Biomaterials | Year: 2014
In this study, human embryonic stem cell-derived cardiomyocytes were seeded onto controlled two-dimensional micropatterned features, and an improvement in sarcomere formation and cell alignment was observed in specific feature geometries. High-resolution photolithography techniques and microcontact printing were utilized to produce features of various rectangular geometries, with areas ranging from 2500μm2 to 160,000μm2. The microcontact printing method was used to pattern non-adherent poly(ethylene glycol) regions on gold coated glass slides. Matrigel and fibronectin extracellular matrix (ECM) proteins were layered onto the gold-coated glass slides, providing a controlled geometry for cell adhesion. We used small molecule-based differentiation and an antibiotic purification step to produce a pure population of immature cardiomyocytes from H9 human embryonic stem cells (hESCs). We then seeded this pure population of human cardiomyocytes onto the micropatterned features of various sizes and observed how the cardiomyocytes remodeled their myofilament structure in response to the feature geometries. Immunofluorescence was used to measure α-actinin expression, and phalloidin stains were used to detect actin presence in the patterned cells. Analysis of nuclear alignment was also used to determine how cell direction was influenced by the features. The seeded cells showed clear alignment with the features, dependent on the width rather than the overall aspect ratio of the features. It was determined that features with widths between 30μm and 80μm promoted highly aligned cardiomyocytes with a dramatic increase in sarcomere alignment relative to the long axis of the pattern. This creation of highly-aligned cell aggregates with robust sarcomere structures holds great potential in advancing cell-based pharmacological studies, and will help researchers to understand the means by which ECM geometries can affect myofilament structure and maturation in hESC-derived cardiomyocytes. © 2014 Elsevier Ltd.
Dasarathy G.,Wisconsin Institutes for Discovery |
Nowak R.,Wisconsin Institutes for Discovery |
Roch S.,University of Wisconsin - Madison
IEEE/ACM Transactions on Computational Biology and Bioinformatics | Year: 2015
We consider the problem of estimating the evolutionary history of a set of species (phylogeny or species tree) from several genes. It is known that the evolutionary history of individual genes (gene trees) might be topologically distinct from each other and from the underlying species tree, possibly confounding phylogenetic analysis. A further complication in practice is that one has to estimate gene trees from molecular sequences of finite length. We provide the first full data-requirement analysis of a species tree reconstruction method that takes into account estimation errors at the gene level. Under that criterion, we also devise a novel reconstruction algorithm that provably improves over all previous methods in a regime of interest. © 2004-2012 IEEE.