Alternative splicing enables a gene translating into different isoforms and into the corresponding proteoforms, which actually accomplish various biological functions of a living body. Isoform-isoform interactions (IIIs) provide a higher resolution interactome to explore the cellular processes and disease mechanisms than the canonically studied protein-protein interactions (PPIs), which are often recorded at the coarse gene level. The knowledge of IIIs is critical to map pathways, understand protein complexity and functional diversity, but the known IIIs are very scanty. In this paper, we propose a deep learning based method called DeepIII to systematically predict genome-wide IIIs by integrating diverse data sources, including RNA-seq datasets of different human tissues, exon array data, domain-domain interactions (DDIs) of proteins, nucleotide sequences and amino acid sequences. Particularly, DeepIII fuses these data to learn the representation of isoform pairs with a four-layer deep neural networks, and then performs binary classification on the learnt representation to achieve the prediction of IIIs. Experimental results show that DeepIII achieves a superior prediction performance to the state-of-the-art solutions and the III network constructed by DeepIII gives more accurate isoform function prediction. Case studies further confirm that DeepIII can differentiate the individual interaction partners of different isoforms spliced from the same gene. The code and datasets of DeepIII are available at http://mlda.swu.edu.cn/codes.php?name=DeepIII.

中文翻译：

---

DeepIII：通过深度神经网络和数据融合预测异构体-异构体交互

选择性剪接使基因能够翻译成不同的亚型并转化为相应的蛋白质形式，它们实际上完成了活体的各种生物学功能。同种型-同种型相互作用 (IIIs) 提供更高分辨率的相互作用组来探索细胞过程和疾病机制，而不是规范研究的蛋白质-蛋白质相互作用 (PPI)，后者通常在粗略的基因水平上记录。IIIs 的知识对于绘制通路、了解蛋白质复杂性和功能多样性至关重要，但已知的 IIIs 非常少。在本文中，我们提出了一种名为 DeepIII 的基于深度学习的方法，通过整合不同的数据源来系统地预测全基因组 III，包括不同人体组织的 RNA-seq 数据集、外显子阵列数据、蛋白质的域域相互作用 (DDI)、核苷酸序列和氨基酸序列。特别，DeepIII 将这些数据融合在一起，用一个四层的深度神经网络学习异构体对的表示，然后对学习的表示进行二进制分类，从而实现对 IIIs 的预测。实验结果表明，DeepIII 实现了优于最先进解决方案的预测性能，并且由 DeepIII 构建的 III 网络提供了更准确的异构函数预测。案例研究进一步证实，DeepIII 可以区分从同一基因剪接的不同亚型的个体相互作用伙伴。DeepIII 的代码和数据集可在 实验结果表明，DeepIII 实现了优于最先进解决方案的预测性能，并且由 DeepIII 构建的 III 网络提供了更准确的异构函数预测。案例研究进一步证实，DeepIII 可以区分从同一基因剪接的不同亚型的个体相互作用伙伴。DeepIII 的代码和数据集可在 实验结果表明，DeepIII 实现了优于最先进解决方案的预测性能，并且由 DeepIII 构建的 III 网络提供了更准确的异构函数预测。案例研究进一步证实，DeepIII 可以区分从同一基因剪接的不同亚型的个体相互作用伙伴。DeepIII 的代码和数据集可在http://mlda.swu.edu.cn/codes.php?name=DeepIII.