Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
- Publication
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Gpu Deconvolution Wow Result On 2048x2048x32 Plane Z-Series, George Mcnamara
Gpu Deconvolution Wow Result On 2048x2048x32 Plane Z-Series, George Mcnamara
George McNamara
GPU Deconvolution WOW result on 2048x2048x32 plane Z-series ... formerly bad academic code ("you get what you pay for") now impressive
Alternative title: "instant gratification quantitative deconvolution fluorescence microscopy".
http://works.bepress.com/gmcnamara/55/
Please see "74"
http://works.bepress.com/gmcnamara/74/
for 32-bit images from this project (bepress file size limitation prevented me from including them in this ZIP archive).
//
Summary: Deconvolution microscopy has historically been painfully slow. The early vendors were:
- Scanalytics (Carrington and Fay), commercialized to try to sell expensive, specialized array processors made by CSPI (the CSPI box likely had less computing power than a first gen smartphone).
- Applied Precision (Sedat …
Deciphering The Associations Between Gene Expression And Copy Number Alteration Using A Sparse Double Laplacian Shrinkage Approach, Shuangge Ma
Shuangge Ma
Both gene expression levels (GEs) and copy number alterations (CNAs) have important implications in the development of complex diseases. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The expression of a gene can be regulated by multiple CNAs, and one CNA can regulate the expression of multiple genes. In addition, multiple GEs (CNAs) can be correlated with each other. The existing methods for associating GEs with CNAs have limitations in deciphering the complex data structures. In this study, we develop a sparse double Laplacian shrinkage approach. It jointly models the effects of …
A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma
A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma
Shuangge Ma
In genetic and genomic studies, gene-environment (G*E) interactions have important implications. Some of the existing G$\times$E interaction methods are limited by analyzing a small number of G factors at a time, by assuming linear effects of E factors, by assuming no data contamination, and by adopting ineffective selection techniques. In this study, we propose a new approach for identifying important G*E interactions. It jointly models the effects of all E and G factors and their interactions. A partially linear varying coefficient model (PLVCM) is adopted to accommodate possible nonlinear effects of E factors. A rank-based loss function is used to …