分子探勘(Molecule mining)為使用分子的數據挖掘。由於分子可由分子圖表示,這與圖形挖掘和結構化數據挖掘密切相關。主要問題是如何在區分數據實例時表示分子。其中一種方法是化學相似性度量,這在化學信息學領域具有悠久的傳統。
計算化學相似性的典型方法是使用化學指紋,但這會導致丟失有關分子拓撲的基礎信息。挖掘分子圖直接避免了這個問題。反向QSAR問題也適用於矢量映射問題。
- MCS-HSCS[9] (單MCS最高得分普通子結構(HSCS)排名策略)
- 小分子子圖檢測器(SMSD)[10]-是一個基於Java的軟件庫,用於計算小分子之間的最大共同子圖(MCS)。這將有助於我們找到兩個分子之間的相似性/距離。 MCS也用於通過擊打分子來篩選藥物化合物,其分享共同的子圖(子結構)。[11]
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