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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Ye, Yuan-Nong Zheng, Liu-Feng Huang, Meng-Ya Liu, Tao Zeng, Zhu Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Guiyang550025 China Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University Guiyang550025 China Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and Engineering Guizhou Medical University Guiyang550025 China

ISBN: (纸本)9783030786144

A complete inpatient electronic medical record contains a lot of information. In recent years, numerous researchers have carried out research on word segmentation of medical texts. Since the medical record text is written by free text, structuring the medical record text is an important part of the medical record intelligent analysis when these medical named entities are recognized. At present, named entity recognition methods are mainly divided into lexicographical and rule-based methods and machine learning-based methods. The machine learn-based approach takes the named entity recognition task as the annotation problem of sequence data, mainly considering the context information. The features commonly used in feature construction are contextual feature and dictionary features. BERT+LSTM+CRF were used to train the named entity recognition model. Open source CRF++ was adopted as the tool we relied on. We trained the LSTM+F model using the results of the original word segmentation and the information in the context as features. We carried out a 5-fold cross validation. The results showed that the overall F-1 score (MICRO-F) of named entity recognition reached 0.92, which confirmed that the model could accurately complete the task of medical named entity recognition. © 2021, Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Impact of Consumer Characteristics on IP Product Purchase: Empirical Evidence from a Chinese Chain Retailer 10

Impact of Consumer Characteristics on IP Product Purchase: E...

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10th International Conference on Information Technology and Quantitative Management, ITQM 2023

作者： Tang, Jiayu Wang, Tingyan Tian, Xin Cai, Qiang Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China Sino-Danish College University of Chinese Academy of Sciences Beijing100190 China Nuffield Department of Medicine University of Oxford South Parks Road OxfordOX1 3SY United Kingdom NIHR Oxford Biomedical Research Centre Big Data Institute University of Oxford Old Road Campus OxfordOX3 7LF United Kingdom School of Economics and Management Ningbo University of Technology Ningbo315211 China

Developing IP product has become a common differentiation strategy for retailers to attract customers and remain competence strength. This study uses empirical model to relate consumer characteristics with IP product purchase. The results show that consumers shopping on weekends are more likely to buy IP products, and consumers who have stocking behavior are less likely to purchase IP products. Consumers who are members of the retailer also have lower probability to buy IP products. These findings provide suggestions for the retailers who want to apply differentiation strategy by introducing co-branded IP products. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International Conference on Information Technology and Quantitative Management.

关键词： Consumer behavior

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Design,methodology,and baseline of whole city‑million scale children and adolescents myopia survey(CAMS)in Wenzhou,China

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Eye and Vision 2021年第1期8卷 303-316页

作者： Liangde Xu Youyuan Zhuang Guosi Zhang Yunlong Ma Jian Yuan Changseng Tu MiaoMiao Li Wencan Wang Yaru Zhang Xiaoyan Lu Jing Li Xinting Liu Zhengbo Xue Meng Zhou Jie Sun Jinhua Bao Ming Li Fan Lu Hong Wang Jianzhong Su Jia Qu School of Ophthalmology and Optometry and Eye Hospital Wenzhou Medical UniversityWenzhou 325027China State Key Laboratory of Ophthalmology Optometry and Visual ScienceWenzhou 325027China Institute of Biomedical Big Data Wenzhou Medical UniversityWenzhou 325027China National Clinical Research Center for Ocular Disease Wenzhou 325027China College of Bioinformatics Science and Technology Harbin Medical UniversityHarbin 150081People’s Republic of China

Background:Myopia is the most common visual impairment in children and adolescents *** study described an economical and effective population-based screening pipeline and performed the project of a million scale children and adolescents myopia survey(CAMS),which will shed light on the further study of myopia from the level of epidemiology and precision ***:We developed a novel population-based screening pattern,an intelligent screening process and internetbased information transmission and analysis system to carry out the survey consisting of school children in Wenzhou,*** examination items include unaided distance visual acuity,presenting distance visual acuity,and noncycloplegic *** and high myopia were defined as spherical equivalent(SE)≤−1.00 diopters(D)and SE≤−6.00 D,***,the reports of the vision checking were automatically sent to parents and the related *** CAMS project will be done two to four times annually with the support of the *** online eyesight status information management system(OESIMS)was developed to construct comprehensive and efficient electronic vision health records(EVHRs)for myopia information inquiry,risk pre-warning,and further ***:The CAMS completed the first-round of screening within 30 days for 99.41%of Wenzhou students from districts and counties,in June 2019.A total of 1,060,925 participants were eligible for CAMS and 1,054,251(99.37%participation rate)were selected through data quality control,which comprised 1305 schools,and 580,609,251,050 and 170,967 elementary,middle,and high school *** mean age of participants was 12.21±3.32 years(6-20 years),the female-to-male ratio was *** prevalence of myopia in elementary,middle,and high school students was 38.16%,77.52%,and 84.00%,respectively,and the high myopia incidence was 0.95%,6.90%,and 12.98%.Conclusions:The CAMS standardized myopia screening model involves automating large-scal

关键词： Baseline Vision screening Myopia prevention and control Population-based

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A Novel Method for Quantitative Evaluation of Anti-Infection Immune Defense Function and its Application

SSRN

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SSRN 2024年

作者： Tan, Zhen-Lin Luo, Tao Wu, Xiao-Jun Lei, Qian Chen, Jie Guo, An-Yuan Department of Laboratory Medicine West China Biomedical Big Data Center West China Hospital Sichuan University Chengdu610041 China Hubei Key Laboratory of Bioinformatics and Molecular-imaging College of Life Science and Technology Huazhong University of Science and Technology Hubei Wuhan430074 China College of Life Sciences University of Chinese Academy of Sciences Beijing101408 China BGI Education Center University of Chinese Academy of Sciences Shenzhen518083 China

ImmuDef is a novel algorithm for precise, quantitative assessment of anti-infection immune defense based on RNA-seq data. Using enrichment scores of immunologic signature gene sets, we defined three feature sets for bacteria, viruses, and fungi infection. Three normalized scores based on modified Manhattan distances were defined as immune scores (IS) to evaluate immunity against these infections. Tested on 3,202 samples across 39 datasets, ImmuDef distinguished well between healthy individuals and patients with AIDS, COVID-19, sepsis, tuberculosis (AUC: 0.71-1.00). It accurately predicted survival and death outcomes in critical sepsis (AUC = 0.89) and severe COVID-19 (AUC = 0.84). In hepatitis B patients, IS was significantly lower in those with active HBV replication and negatively correlated with ALT levels. ImmuDef offers a novel approach for precise measurement of anti-infection immunity, aiding in disease prognosis prediction and individual health status ***: Financial support was provided by the National Natural Science Foundation of China (32370717) and the 1.3.5 project for disciplines of excellence from West China Hospital of Sichuan University (ZYYC23007).Declaration of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this *** Approval: This study was approved by Ethics Committee on biomedical Research West China Hospital of Sichuan University (Reference: HX-IRB-AF-21-V3.0). © 2024, The Authors. All rights reserved.

关键词： COVID-19

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The Algorithms of Predicting Bacterial Essential Genes and NcRNAs by Machine Learning

The Algorithms of Predicting Bacterial Essential Genes and N...

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作者： Yuannong Ye Dingfa Liang Zhu Zeng Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

Essential genes are indispensable for biological survival. Thus it is of great significance to identify and study essential genes. A machine learning method, K-Nearest Neighbor, is used for development of predicting essential bacterial genes. The homologous features, including sequence homology and functional homology, of the bacterial genomes are extracted for determining essential genes. Based on the features, we use K-Nearest Neighbor algorithm for determining of gene function. And we tune the minimum matching parameter(K) in the essential gene predicted model for building an optimal model of the Escherichia coli specificity model. The corresponding optimal parameter(K) is then extended to other bacterial essential genes predicting models. After cross validation, the highest accuracy is 0.89 while K between 5 and 7. Therefore, the features we extracted can increase the accuracy of the bacterial essential gene prediction. In the premise, we found that the prediction accuracy of the prediction model based on K-Nearest Neighbor was not significantly different in different evolutionary distances between organisms in the database and the investigated species. That means the machine learning model can be extended to more distant species. It wills have a better predictive performance for predicting essential genes of distant species than the usual sequence-based methods.

关键词： Essential genes Machine learning KNN

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Optimization of Gene Translation Using SD Complementary Sequences and Double Codons

Optimization of Gene Translation Using SD Complementary Sequ...

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作者： Dingfa Liang Zhumian Huang Liufeng Zheng Yuannong Ye Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

Studies have confirmed that the growth, development and maintenance structure and function of all living organisms are determined by their genes, but the speed of gene translation products is affected by various internal and external factors. Therefore, studying the gene translation speed is extremely important for production and improving the speed through a variety of ways has always been an important subject. In recent years, the found of codon usage bias, t RNA recycling model and SD sequence-like structure provide another way to optimize the translation efficiency. These methods are almost based on codon usage theory to optimize gene sequence to speed up or slow down the translation speed so as to regulate the cell expression and metabolism. This paper is combined the three theories above, aimed at *** to design some reasonable algorithm to optimize gene sequence and thus using codon adaptation index(CAI) to evaluate the optimized effect.

关键词： E.coli Optimization of gene translation efficiency Codon usage bias tRNA-recyling model SD sequence-like structure

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Integrated Helicobacter Pylori Genome database and Its Analysis

Integrated Helicobacter Pylori Genome Database and Its Analy...

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作者： Liufeng Zheng Mujuan Guo Dingfa Liang Yuannong Ye Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

The shape of helicobacter pylori(HP) is usually helical or S-shaped,which makes it to have the feature of highly divergent. Besides, its distribution also is different greatly in space and time, which is the factor to lead to multiple infection. In addition, in the same infected person, multiple infection also appeared in different regions of strain gene infection origin. Therefore, it is of great significance to study the genomic diversity and evolutionary analysis of Helicobacter pylori. In this paper, we are to analyze the homology of multiple sequences using Clustal X1.83 and meanwhile to construct the homologous genome evolutionary tree by MEGA7.0 to analyze the its function. The purpose of this study is to compare the genomic evolutionary differences of Helicobacter pylori among populations in different regions, and to discuss the significance of its infection prevalence and genomic variation in geographical changes, so as to conduct further discussion on the molecular level research mechanism of Helicobacter pylori.

关键词： Helicobacter pylori ClustalX MEGA Genome Phylogenetic tree

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Impact of Consumer Characteristics on IP Product Purchase: Empirical Evidence from a Chinese Chain Retailer

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Procedia Computer Science 2023年 221卷 933-940页

作者： Jiayu Tang Tingyan Wang Xin Tian Qiang Cai Research Center on Fictitious Economy and Data Science. Chinese Academy of Sciences Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Sino-Danish College University of Chinese Academy of Sciences Beijing 100190 China Nuffield Department of Medicine University of Oxford South Parks Road Oxford OX1 3SY United Kingdom NIHR Oxford Biomedical Research Centre Big Data Institute University of Oxford Old Road Campus Oxford OX3 7LF United Kingdom School of Economics and Management Ningbo University of Technology Ningbo 315211 China

关键词： IP product Weekend Stock Membership

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Revelation of Brevi-inflammin, a novel anti-inflammatory metabolite from Brevibacterium casei VRK 1, as a potent COX-2 inhibitor

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Computational Biology and Chemistry 2025年 119卷

作者： Vishnupriya Chandrasekaran Gopinath Samykannu Jeykumar Natarajan Kavitha Rangasamy Biomedical and Microbial Research Laboratory Department of Biochemistry Bharathiar University Coimbatore Tamil Nadu 641 046 India Department of Plant Molecular Biology and Bioinformatics Tamil Nadu Agricultural University Coimbatore Tamil Nadu 641 003 India Data Mining and Text Mining Laboratory Department of Bioinformatics Bharathiar University Coimbatore Tamil Nadu 641 046 India

Non-steroidal anti-inflammatory drugs (NSAIDs) often cause adverse effects, leading to increased interest in the identification of natural compounds with fewer side effects. This study reports the purification and characterization of an alkylated flavonoid, Brevi-inflammin, a novel marine actinobacteria-derived compound that contains anti-inflammatory activity from Brevibacterium casei VRK 1. Using the one-pot synthesis method, the alkylated flavonoid compound Brevi-inflammin was synthesized and purified using semi-preparative reverse-phase HPLC. Further, it is characterized through multiple spectroscopic techniques, including UV–visible spectroscopy, FTIR, HPLC NMR, and UPLC-MS/MS. To assess the anti-inflammatory potential of Brevi-inflammin, the cytotoxic assessment and nitrous oxide inhibitory activity were performed. Further, molecular docking and molecular dynamics simulations were used to evaluate the binding affinity and stability of Brevi-inflammin with a COX-2. Spectroscopic results revealed Brevi-inflammin as an alkylated flavonoid compound, evidenced by its maximum absorption at 230 nm, characteristic aromatic ring structures (CH 2 and CH 3 stretching vibrations), and alkylation signature at 1652 cm −1 . Additionally, HPLC results highlighted Brevi-inflammin as a flavonoid compound. Structural verification through NMR studies confirmed Brevi-inflammin as an alkylated flavonoid. UPLC-MS/MS results confirmed its molecular mass as 279.05  m/z . Cytotoxicity studies proved the compound's safety up to a concentration of 250 μg/mL. The inhibition of nitrous oxide production was observed at a concentration of 1000 µg/mL. Molecular dynamic simulations revealed strong binding interactions between Brevi-inflammin and COX-2, mediated through hydrogen bonds, hydrophobic interactions, and van der Waals forces. Combining experimental and computational approaches, this comprehensive characterization establishes that Brevi-inflammin could be a promising candidate for ant

关键词： Alkylated flavonoids Brevibacterium casei VRK 1 Microbial drugs Molecular dynamics simulation

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A theoretic study of a distance-based regression model

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Science China Mathematics 2019年第5期62卷 979-998页

作者： Jialu Li Wei Zhang Sanguo Zhang Qizhai Li School of Mathematics and Statistics Beijing Institute of Technology Biostatistics and Bioinformatics Branch National Institute of Child Health and Human Development School of Mathematical Sciences University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences LSC NCMIS Academy of Mathematics and Systems Science Chinese Academy of Sciences

The distance-based regression model has many applications in analysis of multivariate response regression in various ?elds, such as ecology, genomics, genetics, human microbiomics, and neuroimaging. It yields a pseudo F test statistic that assesses the relation between the distance(dissimilarity) of the subjects and the predictors of interest. Despite its popularity in recent decades, the statistical properties of the pseudo F test statistic have not been revealed to our knowledge. This study derives the asymptotic properties of the pseudo F test statistic using spectral decomposition under the matrix normal assumption, when the utilized dissimilarity measure is the Euclidean or Mahalanobis distance. The pseudo F test statistic with the Euclidean distance has the same distribution as the quotient of two Chi-squared-type mixtures. The denominator and numerator of the quotient are approximated using a random variable of the form ξχ_d^2+ η, and the approximate error bound is given. The pseudo F test statistic with the Mahalanobis distance follows an F *** simulation studies, the approximated distribution well matched the "exact" distribution obtained by the permutation procedure. The obtained distribution was further validated on H1N1 in?uenza data, aging human brain data, and embryonic imprint data.

关键词： distance-based regression Euclidean pseudo F test statistic Mahalanobis

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