scholarly journals Improved inference of chromosome conformation from images of labeled loci

2018 ◽  
Author(s):  
Brian C. Ross ◽  
James Costello
Keyword(s):  
Large Scale ◽  
Reconstruction Algorithm ◽  
Reconstruction Accuracy ◽  
Chromosome Conformation ◽  
Imaging Technologies ◽  
Link Type ◽  
Large Scale Problems

AbstractWe previously published a method that infers chromosome conformation from images of fluorescently-tagged genomic loci, for the case when there are many loci labeled with each distinguishable color. Here we build on our previous work and improve the reconstruction algorithm to address previous limitations. We show that these improvements 1) increase the reconstruction accuracy and 2) allow the method to be used on large-scale problems involving several hundred labeled loci. Simulations indicate that full-chromosome reconstructions at 1/2 Mb resolution are possible using existing labeling and imaging technologies. The updated reconstruction code and the script files used for this paper are available at: https://github.com/heltilda/align3d.

scholarly journals Improved inference of chromosome conformation from images of labeled loci

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1521
Author(s):  
Brian C. Ross ◽  
James C. Costello
Keyword(s):  
Large Scale ◽  
Reconstruction Algorithm ◽  
Reconstruction Accuracy ◽  
Chromosome Conformation ◽  
Imaging Technologies ◽  
Link Type ◽  
Large Scale Problems

We previously published a method that infers chromosome conformation from images of fluorescently-tagged genomic loci, for the case when there are many loci labeled with each distinguishable color.  Here we build on our previous work and improve the reconstruction algorithm to address previous limitations.  We show that these improvements 1) increase the reconstruction accuracy and 2) allow the method to be used on large-scale problems involving several hundred labeled loci.  Simulations indicate that full-chromosome reconstructions at 1/2 Mb resolution are possible using existing labeling and imaging technologies.  The updated reconstruction code and the script files used for this paper are available at:  https://github.com/heltilda/align3d.

scholarly journals Improved inference of chromosome conformation from images of labeled loci

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1521
Author(s):  
Brian C. Ross ◽  
James C. Costello
Keyword(s):  
Large Scale ◽  
Reconstruction Algorithm ◽  
Reconstruction Accuracy ◽  
Chromosome Conformation ◽  
Imaging Technologies ◽  
Link Type ◽  
Large Scale Problems

We previously published a method that infers chromosome conformation from images of fluorescently-tagged genomic loci, for the case when there are many loci labeled with each distinguishable color.  Here we build on our previous work and improve the reconstruction algorithm to address previous limitations.  We show that these improvements 1) increase the reconstruction accuracy and 2) allow the method to be used on large-scale problems involving several hundred labeled loci.  Simulations indicate that full-chromosome reconstructions at 1/2 Mb resolution are possible using existing labeling and imaging technologies.  The updated reconstruction code and the script files used for this paper are available at:  https://github.com/heltilda/align3d.

scholarly journals Improved inference of chromosome conformation from images of labeled loci

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1521 ◽  
Author(s):  
Brian C. Ross ◽  
James C. Costello
Keyword(s):  
Large Scale ◽  
Reconstruction Algorithm ◽  
Reconstruction Accuracy ◽  
Chromosome Conformation ◽  
Imaging Technologies ◽  
Large Scale Problems

We previously published a method that infers chromosome conformation from images of fluorescently-tagged genomic loci, for the case when there are many loci labeled with each distinguishable color. Here we build on our previous work and improve the reconstruction algorithm to address previous limitations. We show that these improvements 1) increase the reconstruction accuracy and 2) allow the method to be used on large-scale problems involving several hundred labeled loci. Simulations indicate that full-chromosome reconstructions at 1/2 Mb resolution are possible using existing labeling and imaging technologies. The updated reconstruction code and the script files used for this paper are available at: https://github.com/heltilda/align3d.

A new reconstruction algorithm based on temporal neural network and its application in power quality disturbance data

2021 ◽  
pp. 002029402110197
Author(s):  
Yan Liu ◽  
Wei Tang ◽  
Yiduo Luan
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Large Scale ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Reconstruction Accuracy ◽  
Power Quality Disturbance ◽  
Fully Connected ◽  
Reconstruction Model ◽  
Reconstruction Time

The traditional reconstruction algorithms based on p-norm, limited by their reconstruction model and data processing mode, are prone to reconstruction failure or long reconstruction time. In order to break through the limitations, this paper proposes a reconstruction algorithm based on the temporal neural network (TCN). A new reconstruction model based on TCN is first established, which does not need sparse representation and has large-scale parallel processing. Next, a TCN with a fully connected layer and symmetrical zero-padding operation is designed to meet the reconstruction requirements, including non-causality and length-inconsistency. Moreover, the proposed algorithm is constructed and applied to power quality disturbance (PQD) data. Experimental results show that the proposed algorithm can implement the reconstruction task, demonstrating better reconstruction accuracy and less reconstruction time than OMP, ROMP, CoSaMP, and SP. Therefore, the proposed algorithm is more attractive when dictionary design is complicated, or real-time reconstruction is required.

scholarly journals Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Deborah O. Dele-Oni ◽  
Karen E. Christianson ◽  
Shawn B. Egri ◽  
Alvaro Sebastian Vaca Jacome ◽  
Katherine C. DeRuff ◽  
...  
Keyword(s):  
Large Scale ◽  
Cell Model ◽  
Cellular Responses ◽  
Proteomic Profiling ◽  
Reduced Representation ◽  
Link Type ◽  
Original Dataset ◽  
Quality Control Metrics ◽  
Biological Insight ◽  
Chromatin Profiling

AbstractWhile gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of “connectivity” to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics.

scholarly journals Investigation of Improved Cooperative Coevolution for Large-Scale Global Optimization Problems

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 146
Author(s):  
Aleksei Vakhnin ◽  
Evgenii Sopov
Keyword(s):  
Global Optimization ◽  
Evolutionary Algorithms ◽  
Numerical Experiments ◽  
Large Scale ◽  
Optimization Problems ◽  
State Of The Art ◽  
Fixed Number ◽  
High Dimensional ◽  
Cooperative Coevolution ◽  
Large Scale Problems

Modern real-valued optimization problems are complex and high-dimensional, and they are known as “large-scale global optimization (LSGO)” problems. Classic evolutionary algorithms (EAs) perform poorly on this class of problems because of the curse of dimensionality. Cooperative Coevolution (CC) is a high-performed framework for performing the decomposition of large-scale problems into smaller and easier subproblems by grouping objective variables. The efficiency of CC strongly depends on the size of groups and the grouping approach. In this study, an improved CC (iCC) approach for solving LSGO problems has been proposed and investigated. iCC changes the number of variables in subcomponents dynamically during the optimization process. The SHADE algorithm is used as a subcomponent optimizer. We have investigated the performance of iCC-SHADE and CC-SHADE on fifteen problems from the LSGO CEC’13 benchmark set provided by the IEEE Congress of Evolutionary Computation. The results of numerical experiments have shown that iCC-SHADE outperforms, on average, CC-SHADE with a fixed number of subcomponents. Also, we have compared iCC-SHADE with some state-of-the-art LSGO metaheuristics. The experimental results have shown that the proposed algorithm is competitive with other efficient metaheuristics.

Fast Multipole Virtual Boundary Element - Least Square Method for Solving 2-D Elastic Problems

2011 ◽  
Vol 204-210 ◽  
pp. 2196-2201
Author(s):  
Yan Tao Jiang ◽  
Si Tian Chen ◽  
Cheng Hua Li
Keyword(s):  
Boundary Element ◽  
Large Scale ◽  
Fast Multipole Method ◽  
Main Idea ◽  
Least Square Method ◽  
Least Square ◽  
Fast Multipole ◽  
Large Scale Problems ◽  
Virtual Boundary ◽  
Virtual Boundary Element

In this paper, the fast multipole virtual boundary element - least square method (Fast Multipole VBE - LSM) is proposed and used to simulate 2-D elastic problems, which is based on the fast multipole method (FMM) and virtual boundary element - least square method (VBE - LSM).The main idea of the method is to change computational model by applying the FMM to conventional VBE - LSM. The memory and operations could be reduced to be of linear proportion to the degree of freedom (DOF) and large scale problems could be effectively solved on a common desktop with this method. Numerical results show that this method holds virtues of high feasibility, accuracy and efficiency. Moreover, the idea of this method can be generalized and extended in application.

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