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PMDFI: Predicting miRNA–Disease Associations Based on High-Order Feature Interaction

Mingyan Tang, Chenzhe Liu, Dayun Liu, Junyi Liu, Jiaqi Liu, Lei Deng
2021 Frontiers in Genetics  
MicroRNAs (miRNAs) are non-coding RNA molecules that make a significant contribution to diverse biological processes, and their mutations and dysregulations are closely related to the occurrence, development, and treatment of human diseases. Therefore, identification of potential miRNA–disease associations contributes to elucidating the pathogenesis of tumorigenesis and seeking the effective treatment method for diseases. Due to the expensive cost of traditional biological experiments of
more » ... ning associations between miRNAs and diseases, increasing numbers of effective computational models are being used to compensate for this limitation. In this study, we propose a novel computational method, named PMDFI, which is an ensemble learning method to predict potential miRNA–disease associations based on high-order feature interactions. We initially use a stacked autoencoder to extract meaningful high-order features from the original similarity matrix, and then perform feature interactive learning, and finally utilize an integrated model composed of multiple random forests and logistic regression to make comprehensive predictions. The experimental results illustrate that PMDFI achieves excellent performance in predicting potential miRNA–disease associations, with the average area under the ROC curve scores of 0.9404 and 0.9415 in 5-fold and 10-fold cross-validation, respectively.
doi:10.3389/fgene.2021.656107 pmid:33897768 pmcid:PMC8063614 fatcat:gqxl7xqfmvbwjjknwll4y4ij3q

CoqQ: Foundational Verification of Quantum Programs [article]

Li Zhou, Gilles Barthe, Pierre-Yves Strub, Junyi Liu, Mingsheng Ying
2022 arXiv   pre-print
The first one is QHLProver [Liu et al. 2019] , which is used for proving correctness of quantum programs based on quantum Hoare logic.  ...  The QHLProver [Liu et al. 2019 ] is an Isabelle formalization for formal verification of quantum programs based on quantum Hoare logic [Ying 2011 ].  ... 
arXiv:2207.11350v1 fatcat:s3upyahv6vh3jfhemtpzsblmba

An Ontology-driven Framework for Supporting Complex Decision Process [article]

Junyi Chai, James N.K. Liu
2011 arXiv   pre-print
The study proposes a framework of ONTOlogy-based Group Decision Support System (ONTOGDSS) for decision process which exhibits the complex structure of decision-problem and decision-group. It is capable of reducing the complexity of problem structure and group relations. The system allows decision makers to participate in group decision-making through the web environment, via the ontology relation. It facilitates the management of decision process as a whole, from criteria generation,
more » ... evaluation, and opinion interaction to decision aggregation. The embedded ontology structure in ONTOGDSS provides the important formal description features to facilitate decision analysis and verification. It examines the software architecture, the selection methods, the decision path, etc. Finally, the ontology application of this system is illustrated with specific real case to demonstrate its potentials towards decision-making development.
arXiv:1107.2997v1 fatcat:wetwi73h55aqnopzx2g6kmvrdu

Using Junyi Academy to Explore the Difference in Learning Attitude of Remedial Instruction

Yi -Hsueh Shen, Chen-Feng Wu, Li-Hua Liu
2017 INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY  
In this study, Junyi Academy was integrated with the remedial instruction of mathematics.  ...  Another research purpose is to demonstrate that Junyi Academy is feasible for the remedial instruction.  ...  By connecting the computer with Junyi Academy, learners will no longer be confined to a specific space for learning.  ... 
doi:10.24297/ijct.v16i4.6155 fatcat:tufqeyh6hjedhmldw5ftk3ac5i

LLGL2 Increases Ca2+ Influx and Exerts Oncogenic Activities via PI3K/AKT Signaling Pathway in Hepatocellular Carcinoma

Shusheng Leng, Fei Xie, Junyi Liu, Junyi Shen, Guangqian Quan, Tianfu Wen
2021 Frontiers in Oncology  
Dou C, Zhou Z, Xu Q, Liu Z, Zeng Y, Wang Y, et al. Hypoxia-Induced TUFT1 Promotes the Growth and Metastasis of Hepatocellular Carcinoma by Activating the Ca(2+)/PI3K/AKT Pathway.  ...  Xiao S, Chang RM, Yang MY, Lei X, Liu X, Gao WB, et al. Actin-Like 6A Predicts Poor Prognosis of Hepatocellular Carcinoma and Promotes Metastasis and Epithelial-Mesenchymal Transition.  ... 
doi:10.3389/fonc.2021.683629 pmid:34178676 pmcid:PMC8223678 fatcat:jzx4troqhrabdllbyh57j3hn2m

Tonghua Liu: A life dedicated to clinical pathology

Lin Dong, Tanping Fu, Junyi Pang, Zhiyong Liang, Wenli Duan
2018 Protein & Cell  
Liu foresaw the future of biological targeted therapy (Fig. 3) . She put forward the notion that targeted therapy needed targeted diagnosis (Liu, 2008) .  ...  Liu held a great vision for scientific development. In the late 1990s, Prof. Liu sensed the prospects of molecular biology. She sent young pathologists and technicians abroad to study in this field.  ... 
doi:10.1007/s13238-018-0601-0 pmid:30536188 pmcid:PMC6881282 fatcat:vtt7zgnu5ngzzg3n2qphzyampm

IC Neuron: An Efficient Unit to Construct Neural Networks [article]

Junyi An, Fengshan Liu, Jian Zhao, Furao Shen
2020 arXiv   pre-print
As a popular machine learning method, neural networks can be used to solve many complex tasks. Their strong generalization ability comes from the representation ability of the basic neuron model. The most popular neuron is the MP neuron, which uses a linear transformation and a non-linear activation function to process the input successively. Inspired by the elastic collision model in physics, we propose a new neuron model that can represent more complex distributions. We term it Inter-layer
more » ... lision (IC) neuron. The IC neuron divides the input space into multiple subspaces used to represent different linear transformations. This operation enhanced non-linear representation ability and emphasizes some useful input features for the given task. We build the IC networks by integrating the IC neurons into the fully-connected (FC), convolutional, and recurrent structures. The IC networks outperform the traditional networks in a wide range of experiments. We believe that the IC neuron can be a basic unit to build network structures.
arXiv:2011.11271v1 fatcat:27cuuphx5fbtbe2i2yicuohuli

Image Restoration Using Deep Regulated Convolutional Networks [article]

Peng Liu, Xiaoxiao Zhou, Junyi Yang, El Basha Mohammad D, Ruogu Fang
2019 arXiv   pre-print
While the depth of convolutional neural networks has attracted substantial attention in the deep learning research, the width of these networks has recently received greater interest. The width of networks, defined as the size of the receptive fields and the density of the channels, has demonstrated crucial importance in low-level vision tasks such as image denoising and restoration. However, the limited generalization ability, due to the increased width of networks, creates a bottleneck in
more » ... gning wider networks. In this paper, we propose the Deep Regulated Convolutional Network (RC-Net), a deep network composed of regulated sub-network blocks cascaded by skip-connections, to overcome this bottleneck. Specifically, the Regulated Convolution block (RC-block), featured by a combination of large and small convolution filters, balances the effectiveness of prominent feature extraction and the generalization ability of the network. RC-Nets have several compelling advantages: they embrace diversified features through large-small filter combinations, alleviate the hazy boundary and blurred details in image denoising and super-resolution problems, and stabilize the learning process. Our proposed RC-Nets outperform state-of-the-art approaches with significant performance gains in various image restoration tasks while demonstrating promising generalization ability. The code is available at https://github.com/cswin/RC-Nets.
arXiv:1910.08853v1 fatcat:tntspb64nbaj3dhs5jyarivkda

Long-read-based human genomic structural variation detection with cuteSV

Tao Jiang, Yongzhuang Liu, Yue Jiang, Junyi Li, Yan Gao, Zhe Cui, Yadong Liu, Bo Liu, Yadong Wang
2020 Genome Biology  
Long-read sequencing is promising for the comprehensive discovery of structural variations (SVs). However, it is still non-trivial to achieve high yields and performance simultaneously due to the complex SV signatures implied by noisy long reads. We propose cuteSV, a sensitive, fast, and scalable long-read-based SV detection approach. cuteSV uses tailored methods to collect the signatures of various types of SVs and employs a clustering-and-refinement method to implement sensitive SV detection.
more » ... Benchmarks on simulated and real long-read sequencing datasets demonstrate that cuteSV has higher yields and scaling performance than state-of-the-art tools. cuteSV is available at https://github.com/tjiangHIT/cuteSV .
doi:10.1186/s13059-020-02107-y pmid:32746918 fatcat:7ircabbo3jf6vcjbfywfe33cmu

Nonconvex and Nonsmooth Approaches for Affine Chance-Constrained Stochastic Programs [article]

Ying Cui, Junyi Liu, Jong-Shi Pang
2022 arXiv   pre-print
Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due to its possible nondifferentiability and nonconvexity even with simple linear random functionals. Existing approaches for solving the CCPs mainly deal with convex random functionals within the probability function. In the present paper, we consider two generalizations of the class of chance constraints commonly studied in the literature; one generalization involves probabilities of disjunctive nonconvex
more » ... nctional events and the other generalization involves mixed-signed affine combinations of the resulting probabilities; together, we coin the term affine chance constraint (ACC) system for these generalized chance constraints. Our proposed treatment of such an ACC system involves the fusion of several individually known ideas: (a) parameterized upper and lower approximations of the indicator function in the expectation formulation of probability; (b) external (i.e., fixed) versus internal (i.e., sequential) sampling-based approximation of the expectation operator; (c) constraint penalization as relaxations of feasibility; and (d) convexification of nonconvexity and nondifferentiability via surrogation. The integration of these techniques for solving the affine chance-constrained stochastic program (ACC-SP) with various degrees of practicality and computational efforts is the main contribution of this paper.
arXiv:2203.00175v1 fatcat:ajafmftkazd6vglifj5tbg3tiu

Phase-change metasurfaces for dynamic image display and information encryption [article]

Tingting Liu, Zhou Han, Junyi Duan, Shuyuan Xiao
2022 arXiv   pre-print
Optical metasurfaces enable to engineer the electromagnetic space and control light propagation at an unprecedented level, offering a powerful tool to achieve modulation of light over multiple physical dimensions. Here, we demonstrate a Sb_2S_3 phase-change metasurface platform that allows active manipulation of both amplitude and phase. In particular, we implement dynamic nanoprinting and holographic image display through tuning crystallization levels of this phase-change material. The Sb_2S_3
more » ... nanobricks tailored to function the amplitude, geometric and propagation phase modulation constitute the dynamic meta-atoms in the multiplexed metasurfaces. Using the incident polarizations as decoding keys, the encoded information can be reproduced into a naonprinting grayscale image in the near field and two holographic images in the far field. These images can be switched on and off by taking advantages of the reversible tunability of Sb_2S_3 nanostructure between amorphous and crystalline states. The proposed phase-change metasurfaces featuring manifold information and multifold encryption promise ultracompact data storage with high capacity and high security, which suggests an exciting direction for modern cryptography and security applications.
arXiv:2207.08136v1 fatcat:3mevy4peavdwfdu7iz2qclajhi

Application Status of C-phycocyanin in Anti-tumor

LIU Huihui, JIANG Liangqian, WANG Yujuan, LIU Guoxiang, JI Huanhuan, REN Junyi, LI Bing
2018 Zhongliu Fangzhi Yanjiu  
In recent years, the search for anti-tumor drugs with high efficiency, low toxicity and little side effects in marine organisms has attracted the attention of scholars. C-phycocyanin (C-PC) has toxic and side effects on a variety of tumor cells, which can inhibit the growth of tumor cells and promote the apoptosis of tumor cells. Phycocyanin combined with other drugs can improve its anti-tumor activity. This review discusses the therapeutic use of phycocyanin and focuses on the latest advances
more » ... f phycocyanin as a promising natural anti-cancer drug.
doi:10.3971/j.issn.1000-8578.2018.17.1464 doaj:dbd7c17a2db34c56ab5ae27537f7697c fatcat:pqmam6w4ebgfbeb63nrye7fipi

A Review of Acoustic Metamaterials and Phononic Crystals

Junyi Liu, Hanbei Guo, Ting Wang
2020 Crystals  
In 2017, Liu et al. [72] further studied this structure and designed a test device to measure the Doppler effect.  ...  In 2019, Liu et al. [63] designed an acoustic superstructure by embedding multiple acoustic black hole units in an array on a 10 mm thin plate (see Figure 19 ).  ... 
doi:10.3390/cryst10040305 fatcat:dqr4vo2ctfam3dtdle5kpmtnay

Response to Smith's comment

Junyi Liang, Jianyang Xia, Lingli Liu, Shiqiang Wan
2014 Journal of Plant Ecology  
Liang JY, Xia JY, Liu LL, et al. (2013) Global patterns of the responses of leaf-level photosynthesis and respiration in terrestrial plants to experimental warming. J Plant Ecol 6:437-47.  ...  Xie H, Ye JS, Liu XM, et al. (2010) Warming and drying trends on the Tibetan Plateau (1971-2005). Theor Appl Climatol 101:241-53.Downloaded from https://academic.oup.com/jpe/article-  ...  Liang JY, Xia JY, Liu LL, et al. (2013) Global patterns of the responses of leaf-level photosynthesis and respiration in terrestrial plants to experimental warming. J Plant Ecol 6:437-47.  ... 
doi:10.1093/jpe/rtu023 fatcat:ufxe6o3o6jfljdhezowq7yhcca

A Novel Multicriteria Group Decision Making Approach With Intuitionistic Fuzzy SIR Method [article]

Junyi Chai, James N.K. Liu
2011 arXiv   pre-print
The superiority and inferiority ranking (SIR) method is a generation of the well-known PROMETHEE method, which can be more efficient to deal with multi-criterion decision making (MCDM) problem. Intuitionistic fuzzy sets (IFSs), as an important extension of fuzzy sets (IFs), include both membership functions and non-membership functions and can be used to, more precisely describe uncertain information. In real world, decision situations are usually under uncertain environment and involve
more » ... individuals who have their own points of view on handing of decision problems. In order to solve uncertainty group MCDM problem, we propose a novel intuitionistic fuzzy SIR method in this paper. This approach uses intuitionistic fuzzy aggregation operators and SIR ranking methods to handle uncertain information; integrate individual opinions into group opinions; make decisions on multiple-criterion; and finally structure a specific decision map. The proposed approach is illustrated in a simulation of group decision making problem related to supply chain management.
arXiv:1107.1020v1 fatcat:orykhtfepnhj7hvxfsropcms2m
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