Determination of Statistical Properties of Microtubule Populations.

应用数学(英文) Pub Date : 2016-08-01 Epub Date: 2016-08-15 DOI:10.4236/am.2016.713125
Tyson DiLorenzo, Lee Ligon, Donald Drew
{"title":"Determination of Statistical Properties of Microtubule Populations.","authors":"Tyson DiLorenzo,&nbsp;Lee Ligon,&nbsp;Donald Drew","doi":"10.4236/am.2016.713125","DOIUrl":null,"url":null,"abstract":"<p><p>Microtubules are structures within the cell that form a transportation network along which motor proteins tow cargo to destinations. To establish and maintain a structure capable of serving the cell's tasks, microtubules undergo deconstruction and reconstruction regularly. This change in structure is critical to tasks like wound repair and cell motility. Images of fluorescing microtubule networks are captured in grayscale at different wavelengths, displaying different tagged proteins. The analysis of these polymeric structures involves identifying the presence of the protein and the direction of the structure in which it resides. This study considers the problem of finding statistical properties of sections of microtubules. We consider the research done on directional filters and utilize a basic solution to find the center of a ridge. The method processes the captured image by centering a circle around pre-determined pixel locations so that the highest possible average pixel intensity is found within the circle, thus marking the center of the microtubule. The location of these centers allows us to estimate angular direction and curvature of the microtubules, statistically estimate the direction of microtubules in a region of the cell, and compare properties of different types of microtubule networks in the same region. To verify accuracy, we study the results of the method on a test image.</p>","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"7 13","pages":"1456-1475"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528678/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"应用数学(英文)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/am.2016.713125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/8/15 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Microtubules are structures within the cell that form a transportation network along which motor proteins tow cargo to destinations. To establish and maintain a structure capable of serving the cell's tasks, microtubules undergo deconstruction and reconstruction regularly. This change in structure is critical to tasks like wound repair and cell motility. Images of fluorescing microtubule networks are captured in grayscale at different wavelengths, displaying different tagged proteins. The analysis of these polymeric structures involves identifying the presence of the protein and the direction of the structure in which it resides. This study considers the problem of finding statistical properties of sections of microtubules. We consider the research done on directional filters and utilize a basic solution to find the center of a ridge. The method processes the captured image by centering a circle around pre-determined pixel locations so that the highest possible average pixel intensity is found within the circle, thus marking the center of the microtubule. The location of these centers allows us to estimate angular direction and curvature of the microtubules, statistically estimate the direction of microtubules in a region of the cell, and compare properties of different types of microtubule networks in the same region. To verify accuracy, we study the results of the method on a test image.

Abstract Image

Abstract Image

Abstract Image

微管种群统计特性的测定。
微管是细胞内形成运输网络的结构,运动蛋白沿着这个运输网络将货物拖到目的地。为了建立和维持一个能够服务于细胞任务的结构,微管经常经历解构和重建。这种结构的改变对伤口修复和细胞运动等任务至关重要。荧光微管网络的图像以不同波长的灰度捕获,显示不同的标记蛋白质。对这些聚合物结构的分析包括确定蛋白质的存在及其所在结构的方向。本研究考虑了寻找微管截面统计特性的问题。我们考虑了方向滤波器的研究,并利用一个基本的解决方案来寻找脊的中心。该方法通过围绕预先确定的像素位置使圆居中来处理捕获的图像,以便在圆内找到可能的最高平均像素强度,从而标记微管的中心。这些中心的位置使我们能够估计微管的角方向和曲率,统计估计细胞某个区域内微管的方向,并比较同一区域内不同类型微管网络的性质。为了验证该方法的准确性,我们研究了该方法在测试图像上的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
1863
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信