Research And Implementation Of Drug Target Interaction Confidence Measurement Method Based On Causal Intervention

The identification and discovery of drug-target Interaction (DTI) is an important step in the field of Drug research and development, which can help scientists discover new drugs and accelerate the development process. KnowledgeGraph and the related knowledge graph Embedding (KGE) model develop rapidly and show good performance in the field of drug discovery in recent years. In the task of drug target identification, the lack of authenticity and accuracy of the model will lead to the increase of misjudgment rate and the low efficiency of drug development. To solve the above problems, this study focused on the problem of drug target link prediction with knowledge mapping as the core technology, and adopted the confidence measurement method based on causal intervention to measure the triplet score, so as to improve the accuracy of drug target interaction prediction model. By comparing with the traditional Softmax and Sigmod confidence measurement methods on different KGE models, the results show that the confidence measurement method based on causal intervention can effectively improve the accuracy of DTI link prediction, especially for high-precision models. The predicted results are more conducive to guiding the design and development of followup experiments of drug development, so as to improve the efficiency of drug development.Comment: 8 pages,11 figure

Riemannian Natural Gradient Methods

This paper studies large-scale optimization problems on Riemannian manifolds whose objective function is a finite sum of negative log-probability losses. Such problems arise in various machine learning and signal processing applications. By introducing the notion of Fisher information matrix in the manifold setting, we propose a novel Riemannian natural gradient method, which can be viewed as a natural extension of the natural gradient method from the Euclidean setting to the manifold setting. We establish the almost-sure global convergence of our proposed method under standard assumptions. Moreover, we show that if the loss function satisfies certain convexity and smoothness conditions and the input-output map satisfies a Riemannian Jacobian stability condition, then our proposed method enjoys a local linear -- or, under the Lipschitz continuity of the Riemannian Jacobian of the input-output map, even quadratic -- rate of convergence. We then prove that the Riemannian Jacobian stability condition will be satisfied by a two-layer fully connected neural network with batch normalization with high probability, provided that the width of the network is sufficiently large. This demonstrates the practical relevance of our convergence rate result. Numerical experiments on applications arising from machine learning demonstrate the advantages of the proposed method over state-of-the-art ones

Crystal structure, thermal analyses, and acetate binding properties in Zinc(II) complex of a urea-functionalized pyridyl ligand

1302-1310A zinc(II) acetate complex with a urea-functionalized pyridyl ligand, [ZnL2(OAc)2]·2H2O (1) (L = N-(4-chlorophenyl)-N'-(4-pyridyl)urea), has been synthesized by the reaction of L with Zn(OAc)2·2H2O under water-containing condition. X-ray single-crystal diffraction analyses reveal that 2-D sheetlike network structure has been formed by the urea N−H×××Npyridyl interactions and C–H···O interactions in the free ligand L. Complex 1 features 3-D hydrogen bonded network formed by intermolecular N−H···O hydrogen bonds and O−H×××O hydrogen bonds involving urea groups, acetate anions and bridged water molecules. The hydrogen bonds play an important role in stabilizing the supramolecular structures. Thermal gravity analyses have been used to investigate the thermal stabilities of L and 1, and the apparent activation energy (Ea) of the decompositions have also been calculated, and the results indicate that the main decomposition of L needs higher apparent activation energy values Ea than that of 1. The acetate binding properties of L in solution have also been evaluated by Ultraviolet-Visible (UV-Vis) spectroscopy. CCDC: 1506202, L; 1506203, 1