编码生物学的科学计量方法:标题告诉我们关于该领域的信息
1Biodigital Innovation Lab, Translational Biology Department, CUCEI, Universidad de Guadalajara, Mexico.
Bio Systems
|August 9, 2025
概括
代码生物学是一个理解生物信息的框架,是碎片化的. 这项研究绘制了该领域的地图,揭示了24个主题,并强调了跨分子,神经和符号系统的整合模型的需要.
科学领域:
- 跨学科的生物学是跨学科的生物学.
- 生物信息学是一种生物信息学.
- 系统生物学 系统生物学
背景情况:
- 代码生物学研究生命系统中的信息编码,传输和解释.
- 现有的努力编目生物代码,但缺乏对该领域的全面分析.
研究的目的:
- 为编码生物学领域进行第一个全面的科学测量分析.
- 绘制智力景观的地图,并确定关键主题,模式和合作.
主要方法:
- 全文自然语言处理和无监督主题建模应用于策划的出版物库.
- 科学度分析包括时间,地理和协作网络分析.
主要成果:
- 确定了24个不同的主题集群,从分子机制到神经处理和哲学话语.
- 揭示了现场的碎片化以及对整合模型的需求.
- 展示了向系统导向范式的时间转变,并确定了关键的跨学科贡献者.
结论:
- 建立了一个新的代码生物学分支的基础,专注于基于文献的编码过程映射.
- 拟议的未来研究方向,包括神经代码,进化代码和生物/人工编码交叉.
- 要求标准化框架来弥合分子,神经和符号信息处理.
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