Improvement of Accuracy of 3D Structure Reconstruction from Interlaced Video Sequence

2007 ◽  
Author(s):  
Ichiro Yuyama ◽  
Yuta Takano ◽  
Masami Sobata ◽  
Yoko Seki ◽  
Hiroshi Hasegawa ◽  
...  
Keyword(s):  
Video Sequence ◽  
3D Structure ◽  
Structure Reconstruction

scholarly journals Chromatin 3D structure reconstruction with consideration of adjacency relationship among genomic loci

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Fang-Zhen Li ◽  
Zhi-E Liu ◽  
Xiu-Yuan Li ◽  
Li-Mei Bu ◽  
Hong-Xia Bu ◽  
...  
Keyword(s):  
3D Structure ◽  
Structure Reconstruction

2dx - Automated 3D structure reconstruction from 2D crystal data

2008 ◽  
Vol 14 (S2) ◽  
pp. 1290-1291 ◽  
Author(s):  
B Gipson ◽  
X Zeng ◽  
H Stahlberg
Keyword(s):  
New Mexico ◽  
3D Structure ◽  
Crystal Data ◽  
Structure Reconstruction

Extended abstract of a paper presented at Microscopy and Microanalysis 2008 in Albuquerque, New Mexico, USA, August 3 – August 7, 2008

scholarly journals Sensing and Automation in Pruning of Tree Fruit Crops: A Review

2018 ◽  
Author(s):  
Long He ◽  
James Schupp
Keyword(s):  
3D Structure ◽  
Fruit Production ◽  
Robotic Systems ◽  
Fruit Crops ◽  
Short Supply ◽  
End Effector ◽  
Tree Fruit ◽  
Structure Reconstruction ◽  
Human Labor ◽  
Tree Branch

Pruning is one of the most important tree fruit production activities, which is highly dependent on human labor. Skilled labor is in short supply, and the increasing cost of labor is becoming a big issue for the tree fruit industry. Growers are motivated to seek mechanical or robotic solutions for reducing the amount of hand labor required for pruning. This paper reviews the research and development of sensing and automated systems for branch pruning for tree fruit production. Horticultural advancements, pruning strategies, 3D structure reconstruction of tree branches, as well as practice mechanisms or robotics are some of the developments that need to be addressed for an effective tree branch pruning system. Our study summarizes the potential opportunities for automatic pruning with machine-friendly modern tree architectures, previous studies on sensor development, and efforts to develop and deploy mechanical/robotic systems for automated branch pruning. We also describe two examples of qualified pruning strategies that could potentially simplify the automated pruning decision and pruning end-effector design.  Finally, the limitations of current pruning technologies and other challenges for automated branch pruning are described, and possible solutions are discussed.

scholarly journals GSDB: a database of 3D chromosome and genome structures reconstructed from Hi-C data

2019 ◽  
Author(s):  
Oluwatosin Oluwadare ◽  
Max Highsmith ◽  
Jianlin Cheng
Keyword(s):  
Structure Prediction ◽  
Biological Activities ◽  
Genome Structure ◽  
3D Structure ◽  
Three Dimensional ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Reconstruction Methods ◽  
A Genome ◽  
Structure Reconstruction

ABSTRACTAdvances in the study of chromosome conformation capture (3C) technologies, such as Hi-C technique - capable of capturing chromosomal interactions in a genome-wide scale - have led to the development of three-dimensional (3D) chromosome and genome structure reconstruction methods from Hi-C data. The 3D genome structure is important because it plays a role in a variety of important biological activities such as DNA replication, gene regulation, genome interaction, and gene expression. In recent years, numerous Hi-C datasets have been generated, and likewise, a number of genome structure construction algorithms have been developed. However, until now, there has been no freely available repository for 3D chromosome structures. In this work, we outline the construction of a novel Genome Structure Database (GSDB) to create a comprehensive repository that contains 3D structures for Hi-C datasets constructed by a variety of 3D structure reconstruction tools. GSDB contains over 50,000 structures constructed by 12 state-of-the-art chromosome and genome structure prediction methods for publicly used Hi-C datasets with varying resolution. The database is useful for the community to study the function of genome from a 3D perspective. GSDB is accessible at http://sysbio.rnet.missouri.edu/3dgenome/GSDB

3D Structure Reconstruction from Point Correspondences between two Perspective Projections

1994 ◽  
Vol 60 (3) ◽  
pp. 392-397 ◽  
Author(s):  
A. Kara ◽  
D.M. Wilkes ◽  
K. Kawamura
Keyword(s):  
3D Structure ◽  
Structure Reconstruction

scholarly journals ParticleChromo3D: A Particle Swarm Optimization Algorithm for Chromosome and Genome 3D Structure Prediction from Hi-C Data

2021 ◽  
Author(s):  
David Vadnais ◽  
Michael Middleton ◽  
Oluwatosin Oluwadare
Keyword(s):  
Particle Swarm Optimization ◽  
Global Solution ◽  
Genome Structure ◽  
3D Structure ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Candidate Solution ◽  
Structure Reconstruction

AbstractThe three-dimensional (3D) structure of chromatin has a massive effect on its function. Because of this, it is desirable to have an understanding of the 3D structural organization of chromatin. To gain greater insight into the spatial organization of chromosomes and genomes and the functions they perform, chromosome conformation capture techniques, particularly Hi-C, have been developed. The Hi-C technology is widely used and well-known because of its ability to profile interactions for all read pairs in an entire genome. The advent of Hi-C has greatly expanded our understanding of the 3D genome, genome folding, gene regulation and has enabled the development of many 3D chromosome structure reconstruction methods. Here, we propose a novel approach for 3D chromosome and genome structure reconstruction from Hi-C data using Particle Swarm Optimization approach called ParticleChromo3D. This algorithm begins with a grouping of candidate solution locations for each chromosome bin, according to the particle swarm algorithm, and then iterates its position towards a global best candidate solution. While moving towards the optimal global solution, each candidate solution or particle uses its own local best information and a randomizer to choose its path. Using several metrics to validate our results, we show that ParticleChromo3D produces a robust and rigorous representation of the 3D structure for input Hi-C data. We evaluated our algorithm on simulated and real Hi-C data in this work. Our results show that ParticleChromo3D is more accurate than most of the existing algorithms for 3D structure reconstruction. Our results also show that constructed ParticleChromo3D structures are very consistent, hence indicating that it will always arrive at the global solution at every iteration. The source code for ParticleChromo3D, the simulated and real Hi-C datasets, and the models generated for these datasets are available here: https://github.com/OluwadareLab/ParticleChromo3D

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