An Extensive Assessment of Network Embedding in PPI Network Alignment

Network alignment is a fundamental task in network analysis. In the biological field, where the protein–protein interaction (PPI) is represented as a graph, network alignment allowed the discovery of underlying biological knowledge such as conserved evolutionary pathways and functionally conserved proteins throughout different species. A recent trend in network science concerns network embedding, i.e., the modelling of nodes in a network as a low-dimensional feature vector. In this survey, we present an overview of current PPI network embedding alignment methods, a comparison among them, and a comparison to classical PPI network alignment algorithms. The results of this comparison highlight that: (i) only five network embeddings for network alignment algorithms have been applied in the biological context, whereas the literature presents several classical network alignment algorithms; (ii) there is a need for developing an evaluation framework that may enable a unified comparison between different algorithms; (iii) the majority of the proposed algorithms perform network embedding through matrix factorization-based techniques; (iv) three out of five algorithms leverage external biological resources, while the remaining two are designed for domain agnostic network alignment and tested on PPI networks; (v) two algorithms out of three are stated to perform multi-network alignment, while the remaining perform pairwise network alignment.     

PLC远程控制通信程序的设计

计算机通过PPI协议与SIEMENS S7-200系列PLC串行通信不需要PLC方编写通信程序,不占用PLC的系统资源,读写PLC数据快速、可靠.基于此通信技术,用C Builder编写的通信串行程序在多个实际项目中得到了应用,效果良好.     

从形式语义学的角度看汉语时态算子对正极项的允准

极性敏感现象是语言的一种共性。本文通过对汉语中的时态副词的研究,证明了时态副词也是一种正极项,并验证了Ginnakidou[1]所提出的真实性算子对极性敏感项的允准的假说同样适用于解释汉语中的正极项的分布。     

711B1天气雷达回波 PPI 数据显示方法

使用可视化的编程语言在Windows98下对雷达回波PPI二进制数据进行分析,摸清711B1天气雷达回波PPI数据头文件中数据采集时间、天线仰角、扫描半径及二进制数据与回波强度的对应关系,实现雷达图像在Windows下的显示处理,为全州人工影响天气作业决策指挥及短期天气预报提供科学依据。     

A three-phase method for identifying functionally related protein groups in weighted PPI networks

Identifying significant protein groups is of great importance for further understanding protein functions. This paper introduces a novel three-phase heuristic method for identifying such groups in weighted PPI networks. In the first phase a variable neighborhood search (VNS) algorithm is applied on a weighted PPI network, in order to support protein complexes by adding a minimum number of new PPIs. In the second phase proteins from different complexes are merged into larger protein groups. In the third phase these groups are expanded by a number of 2-level neighbor proteins, favoring proteins that have higher average gene co-expression with the base group proteins. Experimental results show that: (i) the proposed VNS algorithm outperforms the existing approach described in literature and (ii) the above-mentioned three-phase method identifies protein groups with very high statistical significance.     

Crystal structure and bonding analysis of the first dinuclear calcium(II)–proton‐pump inhibitor (PPI) `butterfly molecule': a combined microcrystal synchrotron and DFT study

Proton‐pump inhibitors (PPI) are prodrugs used widely to treat acid‐related diseases since the late 1980s. After an extensive research effort it has become clear that the fundamental interactions between metal atoms and PPIs are of paramount importance for both drug release and long‐term therapeutic safety. Unfortunately, until now, very little information has been available on this topic. In this paper, we report the crystal structure analysis of a novel calcium–PPI compound incorporating bridging and terminal deprotonated (R)‐rabeprazole tricyclic ligands (L), namely bis[μ‐(R)‐2‐({[4‐(3‐methoxypropoxy)‐3‐methylpyridin‐2‐yl]methyl}sulfinyl)‐6,7‐dihydro‐3H‐benzofuro[5,6‐d]imidazol‐1‐ido]bis{dimethanol[(R)‐2‐({[4‐(3‐methoxypropoxy)‐3‐methylpyridin‐2‐yl]methyl}sulfinyl)‐6,7‐dihydro‐3H‐benzofuro[5,6‐d]imidazol‐1‐ido]calcium(II)} methanol hexasolvate, [Ca₂(C₂₀H₂₂N₃O₄S)₄(CH₃OH)₄]·6CH₃OH or [Ca₂(L)₄(CH₃OH)₄]·6CH₃OH, which crystallizes from methanol in the polar C2 space group. Using low‐temperature microcrystal synchrotron radiation, we demonstrate that this compound is in the form of a beautiful `butterfly molecule', consisting of a C₂‐symmetric dinuclear (CH₃OH)₂LCa^II(μ₂‐L)₂Ca^IIL(HOCH₃)₂ framework. A large amount of disorder is found within the bridging L ligand and the conformation of the fused tetrahydrofuran ring exhibits great variety. All the sulfinyl groups remain intact and the nonbonded Ca…Ca distance is significantly longer than in other calcium dimers, indicating steric hindrance in the bridging ligands. Considerable hydrogen bonding and aromatic C—H…π interactions co‐operate to stabilize the whole complex, as well as to facilitate supramolecular assembly. Additional investigations into the bond nature were made using density functional theory (DFT) methods at the B3LYP/6‐31G(d) level; geometry optimization, Mulliken atomic charges, MEP (molecular electrostatic potential), HOMO–LUMO (highest occupied molecular orbital–lowest unoccupied molecular orbital), TDOS (total density of states), PDOS (partial density of states), COOP (crystal orbital overlap population) and vibrational spectra were calculated/recorded and assessed carefully.     

Network pharmacology-based approach of novel traditional Chinese medicine formula for treatment of acute skin inflammation in silico

Matrix metalloproteinase-9 (MMP-9) appears to play an important role in acute skin inflammation. Subantimicrobial dose of tetracycline has been demonstrated to inhibit the activity of MMP-9 protein. However, long-term use tetracycline will induce side effect. The catalytic site of MMP-9 is located at zinc-binding amino acids, His401, His405 and His411. We attempted to search novel medicine formula as MMP-9 inhibitors from traditional Chinese medicine (TCM) database by using in silico studies. We utilized high-throughput virtual screening to find which natural compounds could bind to the zinc-binding site. The quantitative structure-activity relationship (QSAR) models, which constructed by scaffold of MMP-9 inhibitors and its activities, were employed to predict the bio-activity of the natural compounds for MMP-9. The results showed that Celacinnine, Lobelanidine and Celallocinnine were qualified to interact with zinc-binding site and displayed well predictive activity. We found that celallocinnine was the best TCM compound for zinc binging sites of MMP-9 because the stable interactions were observed under dynamic condition. In addition, Celacinnine and Lobelanidine could interact with MMP-9 related protein that identified by drug-target interaction network analysis. Thus, we suggested the herbs Hypericum patulum, Sedum acre, and Tripterygium wilfordii that containing Celallocinnine, Celacinnine and Lobelanidine might be a novel medicine formula to avoid the side effect of tetracycline and increase the efficacy of treatment.     

Tomography of functional organization in protein-protein interaction network

In recent years, after high throughput PPI data was available, studies have focused on unraveling how proteins organize their functionality from architecture of the PPI network. We examine the functional organization of a PPI network by dividing the network into layered structure around a protein according to shortest path length. We proposed an index, functional correlation, to assess the functional closeness of a specific protein with its l layer neighbors, i.e. proteins having l shortest path length from the center protein. Our results showed that functional correlation decays exponentially with the number of layers within a characteristic length l_c, and it becomes uncorrelated outside such a characteristic length. A simple model based on functional unit structure was proposed to explain this exponential decay of functional correlation.     

基于炎症反应的阿尔茨海默症功能模块构建

整合阿尔茨海默症患者6个脑区的基因表达数据和蛋白质相互作用数据,较好地避免了基因表达数据高噪声、高变异等不足对构建基因调控网络精度和准确性的影响.考虑到脑部神经炎症是AD发病的重要原因之一,以及钙平衡失调可能是AD几个致病因素联系的纽带,结合蛋白质网络挖掘与AD发病密切相关的基因及炎症和钙离子功能网络,采用最大权重诱导子图(Heinz)算法实现两种高通量数据的结合并提取显著扰动子网,在此基础上利用基于边权的模拟退火算法预测和优化扰动网络,去除网络中较弱的相互作用,添加预测的较强的相互作用,提高网络的精度.实验共提取206个特征基因,并且提取了脑部炎症及钙离子作用机制的功能模块子网.结果证明,使用基于边权的模拟退火算法进一步加强了功能网络的模块性.经生物学分析证明炎症和钙离子机制在AD致病机制中起着很大的作用.这些数据在不同方面为系统地认识基因的复杂调控机制提供了必要的信息.     

Weighted edge based clustering to identify protein complexes in protein–protein interaction networks incorporating gene expression profile

Protein complex detection from protein–protein interaction (PPI) network has received a lot of focus in recent years. A number of methods identify protein complexes as dense sub-graphs using network information while several other methods detect protein complexes based on topological information. While the methods based on identifying dense sub-graphs are more effective in identifying protein complexes, not all protein complexes have high density. Moreover, existing methods focus more on static PPI networks and usually overlook the dynamic nature of protein complexes. Here, we propose a new method, Weighted Edge based Clustering (WEC), to identify protein complexes based on the weight of the edge between two interacting proteins, where the weight is defined by the edge clustering coefficient and the gene expression correlation between the interacting proteins. Our WEC method is capable of detecting highly inter-connected and co-expressed protein complexes. The experimental results of WEC on three real life data shows that our method can detect protein complexes effectively in comparison with other highly cited existing methods.Availability: The WEC tool is available at http://agnigarh.tezu.ernet.in/~rosy8/shared.html.