生信-国科大雁栖湖春季课程《使用生物信息学2：多组学数据整合和挖掘》知识点整理

森林草莓CENH3基因家族的生物信息学分析，马跃，张天龙，CENH3（centromere-specific histone H3 variant）是着丝粒特异性组蛋白H3变异体。在拟南芥中CENH3基因的改造植株与正常野生型杂交能够获得单倍体�

该数据集中所有的鱼的图片都是从水下拍摄的视频中截取的，包含23个种类，总共27370张图像，但是像素很低。数据非常不平衡，其中最常见的鱼图片大约是最不常见鱼的1000倍。所有鱼的种类都有海洋生物学家手动标记。

该书由英国著名生物模型专家J.M.斯密斯所著，是一本绝对值得一读的生物模型专著教材。

基于生物启发式算法的多智能体强化学习算法，强化学习，生物启发算法

基于生物启发式算法的多智能体强化学习算法matlab和python实现

The Python code and supporting material, including example data files, are available as a single ZIP compressed archive. This must be uncompressed before use and will extract into a folder (directory) called "PythonForBiology", inside which the Python files, ending in ".py", and various sub-folders can be found. This arrangement of files and folders will allow the Python code to run directly from inside the uncompressed "PythonForBiology", i.e. the locations of any modules or data files mentioned in the code (and book) are specified relative to this location. The "examples" sub-folder contains all of the data files that are used as examples to support the Python code described in the book. The "databases" sub-folder relates to Chapter 20 and contains SQL and Python files sub-divided into sections to support both SQLite and MySQL database implementations. The "speedy" folder relates to Chapter 27 and contains code relevant to the binding of fast functions written in the C or Cython languages, including any files required for compilation. Many of the book chapters have a corresponding Python file containing the completed scripts and programs for that chapter. These files may be run directly as Python to test the code they contain. Note that several of these files will not work isolation, given that they import functionality from the others, which are assumed to be in the same folder. Chapters 1-4 and 10 do not have a corresponding Python file given that they only discuss the code in terms of short or incomplete fragments.

参考文献：MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction 目的：蛋白质二级结构预测。 上传原因：由于文献中的链接失效，因此将之前下载的开源源码上传。仅限学术研究使用。

专题六-生物除磷工艺.ppt

电化学生物传感器及其在生物医学中的应用，王茜茜，刘宾，本文首先介绍了生物传感器的概念、特点、分类等内容，然后主要介绍酶电化学传感器、免疫电化学生物传感器、适体电化学生物传感器