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The use of gene ontology evidence codes in preventing classifier assessment bias

机译:基因本体证据代码在防止分类器评估偏差中的应用

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摘要

Motivation: The biological community's reliance on computational annotations of protein function makes correct assessment of function prediction methods an issue of great importance. The fact that a large fraction of the annotations in current biological databases are based on computational methods can lead to bias in estimating the accuracy of function prediction methods. This can happen since predicting an annotation that was derived computationally in the first place is likely easier than predicting annotations that were derived experimentally, leading to over-optimistic classifier performance estimates.
机译:动机:生物界对蛋白质功能的计算注释的依赖使对功能预测方法的正确评估成为一个非常重要的问题。当前生物学数据库中大部分注释基于计算方法这一事实可能会导致在估计功能预测方法的准确性方面出现偏差。之所以会发生这种情况,是因为预测最初通过计算得出的注释比预测通过实验得出的注释更容易,从而导致分类器性能估计值过于乐观。

著录项

  • 来源
    《Bioinformatics》 |2009年第9期|p.1173-1177|共5页
  • 作者单位

    1Computer Science Department and 2Statistics Department, Colorado State University, Ft. Collins, CO, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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