Beginner score
78/100
Competition workspace
适合已有深度学习实践基础、愿意使用 PaddlePaddle 2.0 及以上版本的个人参赛者，尤其是想做 RNA 序列与二级结构输入建模的人。参赛者需要能处理 RNA 序列和 LinearFold 预测的二级结构，并输出逐碱基位置的概率向量。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
78/100
Learning value
72/100
Estimated effort
4-12 hours
Metric
Official scoring is published on the Ba…
适合已有深度学习实践基础、愿意使用 PaddlePaddle 2.0 及以上版本的个人参赛者，尤其是想做 RNA 序列与二级结构输入建模的人。参赛者需要能处理 RNA 序列和 LinearFold 预测的二级结构，并输出逐碱基位置的概率向量。
There is a baseline you can run as-is — starting from it is usually far faster than building from scratch.
Training and test RNA datasets
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
PaddlePaddle 2.0+
RNA序列建模
RNA二级结构表示
序列到序列回归
概率值预测
ZIP与TXT结果文件生成
The real friction is usually not library usage. It is validation, time allocation, and task framing.
难点在于把长度可变的 RNA 序列及其 LinearFold 二级结构转化为逐位置预测，并让每个输出都落在 0 到 1 的概率范围内。提交还要求按测试序列编号分别生成单列 TXT 文件并打包为指定名称的 ZIP，格式错误会直接影响提交。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
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