Special Issue, Part 2 18th International Symposium on Bioinformatics Research and Applications (ISBRA 2022)
Special Issue, Part 2 18th International Symposium on Bioinformatics Research and Applications (ISBRA 2022)
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特刊，第 2 部分第 18 届生物信息学研究与应用国际研讨会 (ISBRA 2022)
DOI：
10.1089/cmb.2023.29099.az
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发表时间：
2023
影响因子：
1.7
通讯作者：
Zeilkovsky, Alexander
中科院分区：
文献类型：
--
作者：
Cai, Zhipeng;Skums, Pavel;Zeilkovsky, Alexander
在“SWSNN：一种新型的尖峰神经网络模拟器”一文中，作者提出了一种基于新的中文处理器SW26010pro的快速尖峰神经网络模拟器。论文《HF-DDI：基于多模式混合融合的药物-药物相互作用事件预测》提出了一种基于混合融合的药物-药物相互作用事件预测的深度学习框架。《基于高斯增强表示和对比学习提取突变影响的蛋白质-蛋白质相互作用》一文利用高斯概率分布生成基于BioBERT预训练模型的目标实体表示，用于提取蛋白质-蛋白质相互作用(PPI)。《基于异质蛋白质信息网络的蛋白质复合体识别》中提出的方法结合基因本体属性信息和PPI数据构建异质PPI网络，获取蛋白质节点的矢量表示，识别蛋白质复合体。在《BLASTPhylo--一个用于基因分类和系统发育分析的交互式Web工具》中，作者提出了一个工具，该工具可以直观和交互地显示蛋白质在不同分类级别的分类中的出现情况。“基于蒙特卡罗聚类的病毒变异重建”一文应用最小熵和最小汉明距离蒙特卡罗聚类方法，实现了更准确的宿主内病毒种群的重建。论文《DAHNGC：一种基于异质网络的药物-疾病关联预测的图卷积模型》提出了一种自动学习药物和疾病节点的特征信息的方法，并利用双线性解码器来识别潜在的药物-疾病关联。论文《改进药物相互作用预测的安全多方计算和深度神经网络集成框架》的作者利用秘密共享技术整合了来自多个机构的药物相关特征数据，用于预测药物相互作用。论文《推理引擎：一个基于SMT的离散生物模型推理框架》提出了一个框架，该框架使用一种中间语言来编码部分指定的离散动力系统，从而弥合了领域特定语言和可满足性模理论问题求解器之间的差距。
In “SWsnn: A Novel Simulator for Spiking Neural Networks”, authors present a fast simulator for spiking neural network based on a new Chinese processor, SW26010pro. The paper “HF-DDI: Predicting Drug-Drug Interaction Events Based on Multimodal Hybrid Fusion” proposes a hybrid fusion-based deep learning framework for drug-drug interaction event prediction using various biomedical information about drugs. The paper “Extracting Protein-Protein Interactions Affected by Mutations via Gaussian-enhanced Representation and Contrastive Learning” uses gaussian probability distribution to generate target entity representation based on BioBERT pre-trained model for extracting protein-protein interactions (PPI). The method proposed in “Protein Complex Identification Based on Heterogeneous Protein Information Network” combines Gene Ontology attribute information and PPI data to construct a heterogeneous PPI network, obtains the vector representation of protein nodes and identifies protein complexes. In “BLASTphylo—an Interactive Web Tool for Taxonomic and Phylogenetic Analysis of Genes”, authors present a tool that intuitively and interactively visualizes the protein's occurrence in the taxonomy for different taxonomic ranks. The paper “Reconstruction of Viral Variants via Monte Carlo Clustering” applies minimum entropy and minimum Hamming distance Monte Carlo clustering methods to achieve more accurate reconstruction of intrahost viral populations. The paper “DAHNGC: A Graph Convolution Model for Drug-Disease Association Prediction by using Heterogeneous Network” proposes a method to automatically learn the distinctive information of drug and disease nodes and utilizes a bilinear decoder to identify potential drug-disease association. Authors of the paper “An Integration Framework of Secure Multiparty Computation and Deep Neural Network for Improving Drug-Drug Interaction Predictions” leverage the secret sharing technologies to incorporate the drug-related feature data from multiple institutions for predicting drug-drug interactions. The paper “The Reasoning Engine: An SMT-Based Framework for Reasoning About Discrete Biological Models” proposes a framework that utilizes an intermediate language for encoding partially specified discrete dynamical systems, which bridges the gap between domain specific languages and Satisfiability Modulo Theories problem solvers.