genbio-ai/fluorescence_prediction_rag

荧光预测数据集专注于预测绿色荧光蛋白突变体的荧光强度，这对于生物学研究非常重要，可以帮助研究人员推断细胞系和活体生物中蛋白质的存在。这个回归任务使用训练和评估数据集，其中包含三个或更少突变的突变体，与测试数据集形成对比，后者包含四个或更多突变的突变体。每个实例包括一个表示蛋白质序列的字符串和一个表示蛋白质序列荧光分数的浮点值。数据集分为训练集、验证集和测试集三个部分，分别包含21446、5362和27217个实例。数据来源于TAPE项目，并根据Apache-2.0许可证发布。单序列数据来源于一篇论文。

The Fluorescence Prediction task focuses on predicting the fluorescence intensity of green fluorescent protein mutants, a crucial function in biology that allows researchers to infer the presence of proteins within cell lines and living organisms. This regression task uses training and evaluation datasets that feature mutants with three or fewer mutations, contrasting with the testing dataset, which comprises mutants with four or more mutations. Each instance includes a string representing the protein sequence and a float value indicating the fluorescence score of the protein sequence. The dataset is split into three parts: training set, validation set, and test set, containing 21,446, 5,362, and 27,217 instances respectively. The data is sourced from the TAPE project and is released under the Apache-2.0 License. Single sequence data is collected from a paper.