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Mapping of computational biology research inventions through quantitative patent analysis

机译：通过定量专利分析映射计算生物学研究发明

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Computational biology is relatively a young branch of science, which has experienced tremendous growth in the last two decades. The seeds of this inter-discipline were sown at the end of the seventies, when computers became simpler to use, some biology laboratories decided to adopt them, mainly for storing and managing genomic data. As a result, there was quick completion of projects that would have otherwise taken several years. With a snowballing effect, genome sequencing projects generated large amounts of data whose management required more powerful computers. The advent of the internet has allowed all the research laboratories to share their data, and make them available worldwide through some new genomic and proteomic data banks, such as Gene-Bank, European Molecular Biology Laboratory Data Library and many more. A patent portfolio shows the state of the art of research and development in a specific discipline. Patenting an invention is still tough in many countries, especially when the major part of the claim invention involves mathematical formulae, algorithms and computer programs. These per se are not patentable in many countries; however, they can be protected under copyrights as literary works or trade secrets. It is well known that mathematical formulae, algorithms and computer programs mainly form the core of computational biology. Till date, no study has been made to measure inventive progress in this new inter-discipline. The study shows the research and invention have occurred in a wide range of inter-disciplines, including functional genomics, molecular structure, sequence comparison, molecular simulations, machine learning, data visualization, database development and inventive activity confined to a handful of industrially developed and developing nations, of which majority are privately owned.
机译：计算生物学是相对较年轻的科学分支，这在过去二十年中经历了巨大的增长。这家间学科的种子在七十年代尽头播种，当计算机变得更简单时，一些生物学实验室决定采用它们，主要用于储存和管理基因组数据。因此，快速完成了几年后的项目。具有雪球效应，基因组测序项目产生了大量数据，其管理所需更强大的计算机。互联网的出现允许所有研究实验室分享他们的数据，并通过一些新的基因组和蛋白质组学数据库，如基因库，欧洲分子生物学实验室数据库等，使其提供全球。专利组合显示了特定学科的研究和发展的艺术状态。在许多国家仍然坚硬的专利发明，特别是当所述权利要求的主要部分涉及数学公式，算法和计算机程序时。这些本身在许多国家都不获得专利;但是，它们可以根据文学作品或商业秘密受到保护。众所周知，数学公式，算法和计算机程序主要形成计算生物学的核心。截至日期，未经研究衡量这一新间学科的创造性进展。该研究表明，研究和发明已经发生在广泛的间学科中，包括功能基因组学，分子结构，序列比较，分子模拟，机器学习，数据可视化，数据库开发和创造性局限于少数工业开发和大多数是私人拥有的发展中国家。

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