微管相关蛋白（MAPs）在生长的微管末端的定位

概述

这是一个MATLAB脚本，用于追踪微管相关蛋白（MAPs）在微管末端的位置信息。

系统要求

• MATLAB（建议R2020a或更高版本）
• 图像处理工具箱

数据准备

• 输入格式：TIFF格式的动态影像
• 影像要求：包含清晰的单次结合事件
• 预处理：请先对影像进行去除尺度信息处理

快速开始

1. 导入数据

% 导入微管通道和MAPs通道影像
mymt = tif_img_reader('path_to_microtubule_movie');
mymap = tif_img_reader('path_to_MAPs_movie');

注意：请确保两个通道的帧数和图像尺寸完全一致。

2. 执行追踪

[param_mt, param_map, rel_pos, res_mt, exitflag_mt, arrow_mt] = find_mt_map(mymt, mymap);

程序将显示微管图像，请微管沿微管生长方向绘制线段，完成后双击确认。

3. 验证与数据分析

检查追踪质量：

check_point(mymt, param_mt)    % 查看微管末端追踪
check_point(mymap, param_map)  % 查看MAPs追踪

数据分析流程：

1. 删除结合事件期间追踪不准确的数据点
2. 提取rel_pos第一列在结合时间段内的位置数据
3. 计算这些位置数据的平均值，作为本次结合事件的最终结合位置

输出说明

• rel_pos：相对位置表格，第一列为MAPs结合时间内的位置信息
• param_mt, param_map：拟合参数
• res_mt, exitflag_mt：优化结果和退出标志
• arrow_mt：微管方向信息

注意事项

• 确保影像质量良好，对比度适中
• 绘制方向线时请尽量准确沿微管生长方向
• 建议多次运行验证结果稳定性

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English Version README：

MAPs Tracking Script for Microtubule End Positions

Overview

A MATLAB script designed to track the position information of Microtubule-Associated Proteins (MAPs) at microtubule ends, particularly suitable for analyzing single binding event dynamics.

System Requirements

• MATLAB (R2018a or later recommended)
• Image Processing Toolbox

Data Preparation

• Input format: Dynamic movies in TIFF format
• Movie requirement: Contains clear single binding events
• Preprocessing: Remove scale information before processing

Quick Start

1. Data Import

% Import microtubule channel and MAPs channel movies
mymt = tif_img_reader('path_to_microtubule_movie');
mymap = tif_img_reader('path_to_MAPs_movie');

Note: Ensure both channels have identical frame numbers and image dimensions.

2. Execute Tracking

[param_mt, param_map, rel_pos, res_mt, exitflag_mt, arrow_mt] = find_mt_map(mymt, mymap);

The microtubule image will be displayed. Draw a line along the microtubule growth direction and double-click to confirm.

3. Verification and Data Analysis

Check tracking quality:

check_point(mymt, param_mt)    % Microtubule end tracking
check_point(mymap, param_map)  % MAPs tracking

Data analysis workflow:

1. Remove inaccurate tracking data points during the binding event
2. Extract position data from the first column of rel_pos during binding timeframe
3. Calculate the average value as the final binding position for this event

Output Description

• rel_pos: Relative position table, first column contains position information over time
• param_mt, param_map: Fitting parameters
• res_mt, exitflag_mt: Optimization results and exit flags
• arrow_mt: Microtubule direction information

Notes

• Ensure good image quality with moderate contrast
• Draw direction lines as accurately as possible along microtubule growth direction
• Recommend multiple runs to verify result stability