弱标签学习提升蛋白质功能预测：处理不完整注释的方法

研究论文
0 下载量 53 浏览量 更新于2024-08-27 收藏 2.06MB PDF 举报
"蛋白质功能预测是计算生物学中的一个重要挑战，尤其是在面对大量未标注蛋白时，准确预测其功能至关重要。传统的多标签学习方法通常基于完全标注的假设，即已知功能的蛋白质没有遗漏任何功能。然而，在实际应用中，蛋白质的功能并非总是完全可获取的，可能存在部分缺失的标签或者未知的功能。 本文提出了一种名为Protein Function Prediction with Weak-label Learning (ProWL)的方法，以及其增强版本ProWL-IF，旨在解决蛋白质功能预测中因缺失标注导致的问题。ProWL的核心思想是利用弱标签（weak labels）来填补蛋白质功能的空白，即通过分析部分已知的功能信息，推断可能存在的其他功能。弱标签学习允许模型在一定程度上处理不确定性，提高预测的稳健性。 ProWL-IF在此基础上更进一步，除了补全缺失的功能，它还引入了一个额外的考量——蛋白质不可能具有某些特定功能的知识。这种逆向思维策略可以作为额外的约束，增强模型对蛋白质功能的识别能力。这种方法的优势在于能够充分利用现有的有限信息，并考虑到功能的互补性和排斥性，从而提高预测精度。 实验结果在蛋白质相互作用网络和基因表达数据集上进行了验证，显示ProWL和ProWL-IF在面对不完整标注的情况下，相较于传统方法有显著的优势，能够在实际场景中提供更准确的蛋白质功能预测。这些研究成果对于理解生物系统、疾病机制以及药物设计等领域具有重要意义，也为未来在生物信息学领域中处理复杂、不完整数据提供了新的思路和工具。"

Protein Structure Prediction methods and protocol - David M. Webster

2009-12-23 上传
### 蛋白质结构预测方法与协议 #### 多序列比对——蛋白质结构预测的基础 蛋白质结构预测是生物学领域中的一个重要课题，它涉及到通过计算方法来预测蛋白质三维结构的过程。这一过程对于理解蛋白质的功能、设计...

精简下面表达：Existing protein function prediction methods integrate PPI networks and multivariate bioinformatics data to improve the performance of function prediction. By combining multivariate information, the interactions between proteins become diverse. Different interactions’ functions in functional prediction are various. Combining multiple interactions simply between two proteins can effectively reduce the effect of false negatives and increase the number of predicted functions, but it can also increase the number of false positive functions, which contribute to nonobvious enhancement for the overall functional prediction performance. In this article, we have presented a framework for protein function prediction algorithms based on PPI network and semantic similarity with the addition of protein hierarchical functions to them. The framework relies on diverse clustering algorithms and the calculation of protein semantic similarity for protein function prediction. Classification and similarity calculations for protein pairs clustered by the functional feature are more accurate and reliable, allowing for the prediction of protein function at different functional levels from different proteomes, and giving biological applications greater flexibility.The method proposed in this paper performs well on protein data from wine yeast cells, but how well it matches other data remains to be verified. Yet until now, most unknown proteins have only been able to predict protein function by calculating similarities to their homologues. The predictions result of those unknown proteins without homologues are unstable because they are relatively isolated in the protein interaction network. It is difficult to find one protein with high similarity. In the framework proposed in this article, the number of features selected after clustering and the number of protein features selected for each functional layer has a significant impact on the accuracy of subsequent functional predictions. Therefore, when making feature selection, it is necessary to select as many functional features as possible that are important for the whole interaction network. When an incorrect feature was selected, the prediction results will be somewhat different from the actual function. Thus as a whole, the method proposed in this article has improved the accuracy of protein function prediction based on the PPI network method to a certain extent and reduces the probability of false positive prediction results.

2023-02-27 上传
本文提出了一种基于PPI网络和语义相似性，加上蛋白质分层功能的蛋白质功能预测算法框架，对酒葡萄酵母细胞的蛋白质数据表现出良好的效果，但其他数据的效果如何仍有待验证。此外，该框架中的功能特征选择的数量以及...

请以基于自然语言处理方法在相互作用网络中的蛋白质功能预测为题写一篇论文，并包含参考文献

2023-02-17 上传
Khan, “Protein Function Prediction Using Interaction Network and Natural Language Processing,” in Proceedings of the International Conference on Intelligent Computing, pp. 987-992, 2018. [2] A. M. ...

为什么进不去6mkl.ucsd.edu/dataset/protein-fold-prediction

2023-05-29 上传
可能有多种原因导致你无法访问6mkl.ucsd.edu/dataset/protein-fold-prediction网站。首先，请确保你的网络连接正常，并且你输入的网址正确。如果你确定你的网络连接正常，并且你输入的网址正确，但仍然无法访问该...

from .prediction import make_prediction, make_prediction_v2 ImportError: attempted relative import with no known parent package

2024-04-25 上传
例如，如果你的包名为"mypackage"，你可以使用"from mypackage.prediction import make_prediction, make_prediction_v2"来导入模块。 4. 将模块添加到PYTHONPATH：如果你的模块不在Python的搜索路径中，你可以将...

score threhold

2023-05-04 上传
For example, if the score threshold for a binary classification problem is set to 0.5, any prediction with a score of 0.5 or higher would be considered a positive result, while any prediction with a ...

6mkl.ucsd.edu/dataset/protein-fold-prediction

2023-05-29 上传
这个网站提供了一个蛋白质折叠预测的数据集，其中包含了超过12000个蛋白质序列以及它们的结构信息。这些数据可以用来进行蛋白质折叠预测的研究和开发。这个数据集是由加州大学圣地亚哥分校的研究人员创建的，他们...

prediction interval coverage probability

2023-04-02 上传
such as 95% or 99%, and a prediction interval is constructed based on the model's estimated parameters and the level of uncertainty associated with the predictions. The coverage probability is then ...

与Prediction and risk assessment of extreme weather events based on gumbel copula function类似的文献

2023-03-01 上传
以下是与“Prediction and risk assessment of extreme weather events based on gumbel copula function”类似的文献推荐： 1. "Multivariate Extreme Value Theory for Risk Assessment" by Alexander McNeil, R...

有关于Prophet和transformer模型预测股票的比较新且较优秀的代码推荐吗

2023-05-11 上传
- [Stock Price Prediction with Transformer](https://towardsdatascience.com/stock-price-prediction-with-transformer-architecture-7e2af9c7e361) - 一篇关于使用 Transformer 模型进行股票价格预测的博客，...
weixin_38733281
  • 粉丝: 2
  • 资源: 953
上传资源 快速赚钱

最新资源