GAIN: A graphical method to automatically analyze individual neurite outgrowth

神经突 计算机科学 神经科学 人工智能 生物 生物化学 体外
作者
Byron L. Long,H. Li,Abhinav Mahadevan,Tien T. Tang,Kylie M. Balotin,Nicolas E. Grandel,Jorge A. Soto,Siew Yee Wong,Amada M. Abrego,S. Li,Amina A. Qutub
出处
期刊:Journal of Neuroscience Methods [Elsevier]
卷期号:283: 62-71 被引量:10
标识
DOI:10.1016/j.jneumeth.2017.03.013
摘要

Neurite outgrowth is a metric widely used to assess the success of in vitro neural stem cell differentiation or neuron reprogramming protocols and to evaluate high-content screening assays for neural regenerative drug discovery. However, neurite measurements are tedious to perform manually, and there is a paucity of freely available, fully automated software to determine neurite measurements and neuron counting. To provide such a tool to the neurobiology, stem cell, cell engineering, and neuroregenerative communities, we developed an algorithm for performing high-throughput neurite analysis in immunofluorescent images. Given an input of paired neuronal nuclear and cytoskeletal microscopy images, the GAIN algorithm calculates neurite length statistics linked to individual cells or clusters of cells. It also provides an estimate of the number of nuclei in clusters of overlapping cells, thereby increasing the accuracy of neurite length statistics for higher confluency cultures. GAIN combines image processing for neuronal cell bodies and neurites with an algorithm for resolving neurite junctions. GAIN produces a table of neurite lengths from cell body to neurite tip per cell cluster in an image along with a count of cells per cluster. GAIN's performance compares favorably with the popular ImageJ plugin NeuriteTracer for counting neurons, and provides the added benefit of assigning neurites to their respective cell bodies. In summary, GAIN provides a new tool to improve the robust assessment of neural cells by image-based analysis.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
蔡老八完成签到,获得积分10
2秒前
湖里发布了新的文献求助10
4秒前
Zz发布了新的文献求助10
4秒前
斯文败类应助大胆的灵槐采纳,获得10
5秒前
积极晓绿发布了新的文献求助200
6秒前
6秒前
7秒前
10秒前
13秒前
cz发布了新的文献求助10
14秒前
闫伯涵发布了新的文献求助10
14秒前
15秒前
洁白的宇天完成签到,获得积分10
16秒前
yayaya发布了新的文献求助10
17秒前
17秒前
20秒前
20秒前
小王完成签到,获得积分10
21秒前
21秒前
汉堡包应助谦让夜香采纳,获得10
23秒前
闫伯涵完成签到,获得积分10
23秒前
动听千风发布了新的文献求助10
25秒前
oneJone发布了新的文献求助10
26秒前
NexusExplorer应助cz采纳,获得10
26秒前
XY发布了新的文献求助10
26秒前
27秒前
ERICLEE82完成签到 ,获得积分10
27秒前
30秒前
YaN完成签到 ,获得积分10
30秒前
31秒前
满意嘉熙发布了新的文献求助10
33秒前
张小小发布了新的文献求助60
35秒前
35秒前
Lois_woo发布了新的文献求助10
35秒前
38秒前
赘婿应助科研通管家采纳,获得10
38秒前
鼠霸霸应助科研通管家采纳,获得10
38秒前
我是老大应助科研通管家采纳,获得10
39秒前
慕青应助Gaopkid采纳,获得10
39秒前
wanci应助科研通管家采纳,获得30
39秒前
高分求助中
Sustainability in Tides Chemistry 1500
TM 5-855-1(Fundamentals of protective design for conventional weapons) 1000
CLSI EP47 Evaluation of Reagent Carryover Effects on Test Results, 1st Edition 800
Threaded Harmony: A Sustainable Approach to Fashion 799
Livre et militantisme : La Cité éditeur 1958-1967 500
Retention of title in secured transactions law from a creditor's perspective: A comparative analysis of selected (non-)functional approaches 500
"Sixth plenary session of the Eighth Central Committee of the Communist Party of China" 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3055638
求助须知:如何正确求助?哪些是违规求助? 2712308
关于积分的说明 7430663
捐赠科研通 2357227
什么是DOI,文献DOI怎么找? 1248640
科研通“疑难数据库(出版商)”最低求助积分说明 606766
版权声明 596144