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Global analysis of protein and small-molecule substrates of ubiquitin-like proteins (UBLs)

Molecular & cellular proteomics : MCP 2025年 100975页

作者： Guang-Can Shao Zhen-Lin Chen Shan Lu Qing-Cui Wu Yao Sheng Jing Wang Yan Ma Jian-Hua Sui Hao Chi Xiang-Bing Qi Si-Min He Li-Lin Du Meng-Qiu Dong National Institute of Biological Sciences Beijing 102206 Beijing China. Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS 100190 Beijing China University of Chinese Academy of Sciences Beijing 100049 China. National Institute of Biological Sciences Beijing 102206 Beijing China Tsinghua Institute of Multidisciplinary Biomedical Research Tsinghua University 102206 Beijing China. University of Chinese Academy of Sciences Beijing 100049 China. Electronic address: smhe@***. Tsinghua Institute of Multidisciplinary Biomedical Research Tsinghua University 102206 Beijing China. Electronic address: dulilin@***. Tsinghua Institute of Multidisciplinary Biomedical Research Tsinghua University 102206 Beijing China. Electronic address: dongmengqiu@***.

Ubiquitin-like proteins (UBLs) constitute a family of evolutionarily conserved proteins that share similarities with ubiquitin in 3D structures and modification mechanisms. For most UBLs including Small-Ubiquitin-like Modifiers (SUMO), their modification sites on substrate proteins cannot be identified using the mass spectrometry-based method that has been successful for identifying ubiquitination sites, unless a UBL protein is mutated accordingly. To identify UBL modification sites without having to mutate UBL, we have developed a dedicated search engine pLink-UBL on the basis of pLink, a software tool for identification of cross-linked peptide pairs. pLink-UBL exhibited superior precision, sensitivity, and speed than "make-do" search engines such as MaxQuant, pFind, and pLink. For example, compared to MaxQuant, pLink-UBL increased the number of identified SUMOylation sites by 50 ∼ 300% from the same datasets. Additionally, we present a method for identifying small-molecule modifications of UBLs. This method involves antibody enrichment of a UBL C-terminal peptide following enrichment of a UBL protein, followed by LC-MS/MS analysis and a pFind 3 blind search to identify unexpected modifications. Using this method, we have discovered non-protein substrates of SUMO, of which spermidine is the major one for fission yeast SUMO Pmt3. Spermidine can be conjugated to the C-terminal carboxylate group of Pmt3 through its N or also likely, N amino group in the presence of SUMO E1, E2, and ATP. Pmt3-spermidine conjugation does not require E3 and can be reversed by SUMO isopeptidase Ulp1. SUMO-spermidine conjugation is present in mice and humans. Also, spermidine can be conjugated to ubiquitin in vitro by E1 and E2 in the presence of ATP. The above observations suggest that spermidine may be a common small molecule substrate of SUMO and possibly ubiquitin across eukaryotic species.

关键词： UBL antibody mass spectrometry pLink-UBL spermidine substrates

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Horizontal Positioning and Anti-swinging Control Tower Crane Using Adaptive Sliding Mode Control

Horizontal Positioning and Anti-swinging Control Tower Crane...

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第30届中国控制与决策会议

作者： Wen Wen Bai Hai-Peng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology

As a non-linear underactuated system, the tower crane should be controlled to transport the load to reference position quickly and smoothly. The actual tower crane is susceptible to the environment interference during operation. Conventional Proportion Integral Derivative（PID） controller cannot deal with this interference. Sliding mode control（SMC） is robust to system uncertainties and external disturbances, but it needs to know the upper bounds of uncertainties and external perturbations, which are usually unknown in practical systems. Adaptive backstepping sliding mode control（ABSMC） is used to adaptively estimate the uncertainties and external disturbances, and the stability of the system is proved based on Lyapunov theory. Compared with SMC, the proposed ABSMC has strong robustness.

关键词： tower crane Proportion Integral Derivative Sliding mode control Adaptive backstepping sliding mode control

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Knowledge Reasoning Based on Knowledge Graph

Knowledge Reasoning Based on Knowledge Graph

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2018 3rd International Conference on Advances in Materials,Mechatronics and Civil Engineering(ICAMMCE 2018)

作者： Tian Chujun Yu Hongzhi Meng Xianghe Key Laboratory of National language intelligent processing Key Lab of China's National Linguistic Information Technology

Nowadays, with the rapid development of Internet technology and application mode, the scale of Internet data is growing geometrically, and a large number of valuable knowledge are also in it. How to organize and express these knowledge and carry out in-depth calculation and analysis have aroused widespread concern. Grow up under the environment. Knowledge reasoning based on knowledge graph is one of the hotspots in knowledge graph research. It plays an important role in vertical search, intelligent answering and other applications. Knowledge reasoning oriented to knowledge graph aims at reasoning out new knowledge or identifying wrong knowledge based on existing knowledge. Unlike traditional knowledge reasoning, the knowledge reasoning method facing knowledge graph is also more diverse because of the concise, flexible and flexible knowledge representation in knowledge graph. This article will be based on the basic knowledge reasoning. The concept of knowledge based knowledge reasoning is introduced in recent years. In particular, knowledge reasoning can be divided into single step and multistep reasoning, because the methods are not the same. Each class can be divided into rule based reasoning, distributed representation, reasoning based on the divine network, and mixed reasoning.

关键词： Knowledge Reasoning Knowledge Graph Rule Reasoning Neural Network

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Incremental transformer with deliberation decoder for document grounded conversations

arXiv

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arXiv 2019年

作者： Li, Zekang Niu, Cheng Meng, Fandong Feng, Yang Li, Qian Zhou, Jie Dian Group School of Electronic Information and Communications Huazhong University of Science and Technology Pattern Recognition Center WeChat AI Tencent Inc China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Engineering Northeastern University China

Document Grounded Conversations is a task to generate dialogue responses when chatting about the content of a given document. Obviously, document knowledge plays a critical role in Document Grounded Conversations, while existing dialogue models do not exploit this kind of knowledge effectively enough. In this paper, we propose a novel Transformerbased architecture for multi-turn document grounded conversations. In particular, we devise an Incremental Transformer to encode multi-turn utterances along with knowledge in related documents. Motivated by the human cognitive process, we design a two-pass decoder (Deliberation Decoder) to improve context coherence and knowledge correctness. Our empirical study on a real-world Document Grounded Dataset proves that responses generated by our model significantly outperform competitive baselines on both context coherence and knowledge relevance. Copyright © 2019, The Authors. All rights reserved.

关键词： Decoding

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Jacobi Spectral Collocation Method Based on Lagrange Interpolation Polynomials for Solving Nonlinear Fractional Integro-Differential Equations

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Advances in Applied Mathematics and Mechanics 2018年第6期10卷 1440-1458页

作者： Xingfa Yang Yin Yang Yanping Chen Jie Liu State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082HunanChina Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105HunanChina School of Mathematical Sciences South China Normal UniversityGuangzhou 510631GuangdongChina Center for Research on Leading Technology of Special Equipment School of Mechanical and Electric EngineeringGuangzhou UniversityGuangzhou 510006GuangdongChina

In this paper,we study a class of nonlinear fractional integro-differential equations,the fractional derivative is described in the Caputo *** the properties of the Caputo derivative,we convert the fractional integro-differential equations into equivalent integral-differential equations of Volterra type with singular kernel,then we propose and analyze a spectral Jacobi-collocation approximation for nonlinear integro-differential equations of Volterra *** provide a rigorous error analysis for the spectral methods,which shows that both the errors of approximate solutions and the errors of approximate fractional derivatives of the solutions decay exponentially in L^(∞)-norm and weighted L^(2)-norm.

关键词： Spectral method nonlinear fractional derivative Volterra integro-differential equations Caputo derivative

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Dynamic maintenance of decision rules for decision attribute values’ changing 25th

Dynamic maintenance of decision rules for decision attribute...

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25th International Conference on Neural Information processing, ICONIP 2018

作者： Wang, Yingyao Dai, Jianhua Shi, Hong School of Computer Science and Technology Tianjin University Tianjin300350 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha410081 China

ISBN: (纸本)9783030041816

Rule induction method based on rough set theory (RST) which can generate a minimal set of decision rules by using attribute reduction and approximations has received much attention recently. In real-life, the variation of objects, attributes and attributes’ values affects reducts and approximations, e.g., the coarsening and refining of attributes’ values. The goal of this paper is dynamic maintenance of decision rules for decision attribute values’ coarsening and refining. Two incremental rough-set based methods are proposed to deal with this issue by updating assignment discernibility matrix dynamically without recomputing the reducts from the beginning, which increases the efficiency. © Springer Nature Switzerland AG 2018.

关键词： Rough set theory

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Label distribution learning based on ensemble neural networks 25th

Label distribution learning based on ensemble neural network...

引用

25th International Conference on Neural Information processing, ICONIP 2018

作者： Zhai, Yansheng Dai, Jianhua Shi, Hong School of Computer Science and Technology Tianjin University Tianjin300350 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha410081 China

ISBN: (纸本)9783030041816

Label distribution learning (LDL), as an extension of multi-label learning, is a new arising machine learning technique to deal with label ambiguity problems. The maximum entropy model is commonly used in label distribution learning. However, it does not consider the correlation between the labels and is not suitable for nonlinear relationships, and the prediction performance is also limited. In this paper, we propose a label distribution learning algorithm based on ensemble neural networks. The algorithm trains neural networks with preferences using training sets with different label sets to construct base learners, and combines the base learners with the weights, which is learned by the combined learner to obtain the final learning results. Experimental results show that the proposed algorithm is effective for label distribution data. © Springer Nature Switzerland AG 2018.

关键词： Learning algorithms

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Food recommendation: Framework, existing solutions and challenges

arXiv

引用

arXiv 2019年

作者： Min, Weiqing Jiang, Shuqiang Jain, Ramesh Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science University of California IrvineCA United States

A growing proportion of the global population is becoming overweight or obese, leading to various diseases (e.g., diabetes, ischemic heart disease and even cancer) due to unhealthy eating patterns, such as increased intake of food with high energy and high fat. Food recommendation is of paramount importance to alleviate this problem. Unfortunately, modern multimedia research has enhanced the performance and experience of multimedia recommendation in many fields such as movies and POI, yet largely lags in the food domain. This article proposes a unified framework for food recommendation, and identifies main issues affecting food recommendation including building the personal model, analyzing unique food characteristics, incorporating various context and domain knowledge. We then review existing solutions for these issues, and finally elaborate research challenges and future directions in this field. To our knowledge, this is the first survey that targets the study of food recommendation in the multimedia field and offers a collection of research studies and technologies to benefit researchers in this field. Copyright © 2019, The Authors. All rights reserved.

关键词： Domain Knowledge

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In Vitro Fertilization (IVF) cumulative pregnancy rate prediction from basic patient characteristics

arXiv

引用

arXiv 2019年

作者： Zhang, Bo Cui, Yuqi Wang, Meng Li, Jingjing Jin, Lei Wu, Dongrui Reproductive Medicine Center Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei430030 China Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

Tens of millions of women suffer from infertility worldwide each year. In vitro fertilization (IVF) is the best choice for many such patients. However, IVF is expensive, time-consuming, and both physically and emotionally demanding. The first question that a patient usually asks before the IVF is how likely she will conceive, given her basic medical examination information. This paper proposes three approaches to predict the cumulative pregnancy rate after multiple oocyte pickup cycles. Experiments on 11,190 patients showed that first clustering the patients into different groups and then building a support vector machine model for each group can achieve the best overall performance. Our model could be a quick and economic approach for reliably estimating the cumulative pregnancy rate for a patient, given only her basic medical examination information, well before starting the actual IVF procedure. The predictions can help the patient make optimal decisions on whether to use her own oocyte or donor oocyte, how many oocyte pickup cycles she may need, whether to use embryo frozen, etc. They will also reduce the patient's cost and time to pregnancy, and improve her quality of life. Copyright © 2019, The Authors. All rights reserved.

关键词： Obstetrics

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Object Detection Algorithm for Improving Non-Maximum Suppression Using GIoU

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IOP Conference Series: Materials Science and Engineering 2020年第1期790卷

作者： Zhiqiang Hou Xiaoyi Liu Lilin Chen College of Computer Science and Technology Xian University of Posts and Telecommunications Xi'an China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi'an China

To address the problem of object miss detection and object false detection in single threshold-Non-Maximum Suppression algorithm, this paper proposed a GDT-NMS (Generalized Intersection over Union Dual Threshold NMS, GDT-NMS)) algorithm which using GIoU(Generalized Intersection over Union). Using the GIoU indicator computing the similarity between objects, can better describe the relative position and overlap between the objects. And we proposed the dual-threshold NMS algorithm, which can balance the relationship between the object missed detection problem and the object false detection problem, reduce 'false positive example' problem. By nonlinearly processing the weight function, the object is better distinguished. The algorithm uses Faster R-CNN as the detector. The experimental results show that the improved algorithm has outstanding performance.

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