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342 results on '"Ding, Guohui"'

1. A New Neural Network Model Based on Attention Mechanism that Embeds LSTM into RNN for Nonlinear Time-Lag System Identification

Author

Sun, Lulu, Ding, Guohui, Geng, Shizhan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, You, Peng, editor, Liu, Shuaiqi, editor, and Wang, Jun, editor

Published
2024
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2. SuperTML-Clustering: Two-Dimensional Word Embedding for Structured Tabular Data

Author

Zhang, Jiahao, Ding, Guohui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, You, Peng, editor, Liu, Shuaiqi, editor, and Wang, Jun, editor

Published
2024
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4. Graph Fusion Multimodal Named Entity Recognition Based on Auxiliary Relation Enhancement

Author

Ding, Guohui, Tang, Wenjing, Yuan, Zhaoyi, Sun, Lulu, Fan, Chunlong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Xiaochun, editor, Suhartanto, Heru, editor, Wang, Guoren, editor, Wang, Bin, editor, Jiang, Jing, editor, Li, Bing, editor, Zhu, Huaijie, editor, and Cui, Ningning, editor

Published
2023
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5. Semantic Extension for Cross-Modal Retrieval of Medical Image-Diagnosis Report

Author

Ding, Guohui, Zhang, Qi, Geng, Shizhan, Fan, Chunlong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Fei, editor, Duan, Nan, editor, Xu, Qingting, editor, and Hong, Yu, editor

Published
2023
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6. Cooperative Control of Mobile Robots with Stackelberg Learning

Author

Koh, Joewie J., Ding, Guohui, Heckman, Christoffer, Chen, Lijun, and Roncone, Alessandro

Subjects
Computer Science - Robotics, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Computer Science - Multiagent Systems, I.2.9, I.2.6, I.2.11
Abstract

Multi-robot cooperation requires agents to make decisions that are consistent with the shared goal without disregarding action-specific preferences that might arise from asymmetry in capabilities and individual objectives. To accomplish this goal, we propose a method named SLiCC: Stackelberg Learning in Cooperative Control. SLiCC models the problem as a partially observable stochastic game composed of Stackelberg bimatrix games, and uses deep reinforcement learning to obtain the payoff matrices associated with these games. Appropriate cooperative actions are then selected with the derived Stackelberg equilibria. Using a bi-robot cooperative object transportation problem, we validate the performance of SLiCC against centralized multi-agent Q-learning and demonstrate that SLiCC achieves better combined utility., Comment: 8 pages, 7 figures

Published
2020
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7. Distributed Reinforcement Learning for Cooperative Multi-Robot Object Manipulation

Author

Ding, Guohui, Koh, Joewie J., Merckaert, Kelly, Vanderborght, Bram, Nicotra, Marco M., Heckman, Christoffer, Roncone, Alessandro, and Chen, Lijun

Subjects
Computer Science - Robotics, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Computer Science - Multiagent Systems, I.2.9, I.2.6, I.2.11
Abstract

We consider solving a cooperative multi-robot object manipulation task using reinforcement learning (RL). We propose two distributed multi-agent RL approaches: distributed approximate RL (DA-RL), where each agent applies Q-learning with individual reward functions; and game-theoretic RL (GT-RL), where the agents update their Q-values based on the Nash equilibrium of a bimatrix Q-value game. We validate the proposed approaches in the setting of cooperative object manipulation with two simulated robot arms. Although we focus on a small system of two agents in this paper, both DA-RL and GT-RL apply to general multi-agent systems, and are expected to scale well to large systems., Comment: 3 pages, 3 figures

Published
2020

8. Towards Scalable Koopman Operator Learning: Convergence Rates and A Distributed Learning Algorithm

Author

Liu, Zhiyuan, Ding, Guohui, Chen, Lijun, and Yeung, Enoch

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning
Abstract

We propose an alternating optimization algorithm to the nonconvex Koopman operator learning problem for nonlinear dynamic systems. We show that the proposed algorithm will converge to a critical point with rate $O(1/T)$ and $O(\frac{1}{\log T})$ for the constant and diminishing learning rates, respectively, under some mild conditions. To cope with the high dimensional nonlinear dynamical systems, we present the first-ever distributed Koopman operator learning algorithm. We show that the distributed Koopman operator learning has the same convergence properties as the centralized Koopman operator learning, in the absence of optimal tracker, so long as the basis functions satisfy a set of state-based decomposition conditions. Numerical experiments are provided to complement our theoretical results., Comment: 8 pages, 2 figures

Published
2019

10. Signal-Anticipation in Local Voltage Control in Distribution Systems

Author

Liu, Zhiyuan, You, Seungil, Zhou, Xinyang, Ding, Guohui, and Chen, Lijun

Subjects
Mathematics - Optimization and Control
Abstract

We consider the signal-anticipating behavior in local Volt/Var control for distribution systems. Such a behavior makes interaction among the nodes a game. We characterize Nash equilibrium of the game as the optimum of a global optimization problem and establish its asymptotic global stability. We also show that the signal-anticipating voltage control has less restrictive convergence condition than the signal-taking control. We then introduce the notion of Price of Signal-Anticipation (PoSA) to characterize the impact of signal-anticipating control, and use the gap in cost between network equilibrium in the signal-taking control and Nash equilibrium in the signal-anticipating control as the metric for PoSA. We characterize how the PoSA scales with the size, topology, and heterogeneity of the distribution network for a few network settings. Our results show that the PoSA is upper bounded by a constant and the average PoSA per node will go to zero as the size of the network increases. This is desirable as it means that the PoSA will not be arbitrarily large, no matter what the size of the network is, and no mechanism is needed to mitigate the signal-anticipating behavior. We further carry out numerical experiments with a real-world distribution circuit to complement the theoretical analysis.

Published
2018
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12. Time Series Data Cleaning Based on Dynamic Speed Constraints

Author

Ding, Guohui, Li, Chenyang, Wei, Ru, Sun, Shasha, Liu, Zhaoyu, Fan, Chunlong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, Zhisheng, editor, Beek, Wouter, editor, Wang, Hua, editor, Zhou, Rui, editor, and Zhang, Yanchun, editor

Published
2020
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14. High‐Efficiency Dephosphorization by Bottom‐Blown O2‐CaO Process for Semi‐Steelmaking.

Author

Wang, Chunyang, Dong, Kai, Xue, Zhitao, Zhao, Changliang, Guan, Shunkuan, Ding, Guohui, Feng, Chao, and Zhu, Rong

Subjects
SLAG, KINETIC energy, BASICITY, STEEL manufacture, OXIDATION
Abstract

In steelmaking, the bottom‐blown O2‐CaO process is used to achieve efficient dephosphorization. However, few studies have applied it to dephosphorization converters. Therefore, this study considers the thermodynamic and kinetic mechanisms of dephosphorization during the process. The selective oxidation transfer temperatures of C and P are calculated. Compared to the combined blowing process, the bottom‐blown O2‐CaO process reduces the optimum dephosphorization temperature from 1593 to 1573 K. Moreover, the FeO content decreases by 20.7% owing to the increased stirring energy and improved kinetic conditions; the binary basicity (R) of the slag increases, and the lime consumption decreases by 2.9 kg t−1. The higher slagging efficiency indicates that the CaO powder melts and dephosphorization is completed during the fire‐spot zone floating process. Furthermore, the optimum FeO content for dephosphorization decreases as R increases. The selective oxidation of C and P can be divided into two stages. The oxidation stage of P preferred C is extended in this process. Overall, the end‐point P content accounts for 22.52% and 46.85% of the samples prepared using the combined blowing and bottom‐blown O2‐CaO processes when the P content is 0.02–0.03%, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Indoor phenotyping platforms and associated trait measurement: Progress and prospects

Author

Xu Lingxiang, Chen Jiawei, Ding Guohui, Lu Wei, Ding Yanfeng, Zhu Yan, and Ji Zhou

Subjects
plant phenomics, indoor phenotyping platform, yield-related traits, quality-related traits, resistance-related phenotypes, phenotyping data management and phenotypic analysis, Agriculture (General), S1-972, Technology (General), T1-995
Abstract

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perspectivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorized according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future.

Published
2020
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18. Experience Report: Application of Falsification Methods on the UxAS System

Author

Tuncali, Cumhur Erkan, Hoxha, Bardh, Ding, Guohui, Fainekos, Georgios, Sankaranarayanan, Sriram, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Dutle, Aaron, editor, Muñoz, César, editor, and Narkawicz, Anthony, editor

Published
2018
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20. Exploiting Non-visible Relationship in Link Prediction Based on Asymmetric Local Random Walk

Author

Fan, Chunlong, Li, Dong, Teng, Yiping, Fan, Dongwan, Ding, Guohui, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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21. Whole-genome sequencing of 128 camels across Asia reveals origin and migration of domestic Bactrian camels

Author

Ming, Liang, Yuan, Liyun, Yi, Li, Ding, Guohui, Hasi, Surong, Chen, Gangliang, Jambl, Tuyatsetseg, Hedayat-Evright, Nemat, Batmunkh, Mijiddorj, Badmaevna, Garyaeva Khongr, Gan-Erdene, Tudeviin, Ts, Batsukh, Zhang, Wenbin, Zulipikaer, Azhati, Hosblig, Erdemt, Natyrov, Arkady, Mamay, Prmanshayev, Narenbatu, Meng, Gendalai, Narangerel, Choijilsuren, Khongorzul, Orgodol, He, Jing, Hai, Le, Lin, Weili, Sirendalai, Sarentuya, Aiyisi, Li, Yixue, Wang, Zhen, and Jirimutu

Published
2020
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24. Schema Matching Based on Source Codes

Author

Ding, Guohui, Wang, Guoren, Fan, Chunlong, Chen, Shuo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, An, editor, Ishikawa, Yoshiharu, editor, Qian, Tieyun, editor, Nutanong, Sarana, editor, and Cheema, Muhammad Aamir, editor

Published
2015
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30. Appearance-Order-Based Schema Matching

Author

Ding, Guohui, Dong, Han, Wang, Guoren, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lee, Sang-goo, editor, Peng, Zhiyong, editor, Zhou, Xiaofang, editor, Moon, Yang-Sae, editor, Unland, Rainer, editor, and Yoo, Jaesoo, editor

Published
2012
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31. Discovering Implicit Categorical Semantics for Schema Matching

Author

Ding, Guohui, Wang, Guoren, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Yu, Jeffrey Xu, editor, Kim, Myoung Ho, editor, and Unland, Rainer, editor

Published
2011
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32. Top-K Generation of Mediated Schemas over Multiple Data Sources

Author

Ding, Guohui, Wang, Guoren, Wang, Bin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yoshikawa, Masatoshi, editor, Meng, Xiaofeng, editor, Yumoto, Takayuki, editor, Ma, Qiang, editor, Sun, Lifeng, editor, and Watanabe, Chiemi, editor

Published
2010
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33. Automatic Multi-schema Integration Based on User Preference

Author

Ding, Guohui, Wang, Guoren, Xin, Junchang, Geng, Huichao, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Chen, Lei, editor, Tang, Changjie, editor, Yang, Jun, editor, and Gao, Yunjun, editor

Published
2010
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42. Hyperlipidemia-associated gene variations and expression patterns revealed by whole-genome and transcriptome sequencing of rabbit models

Author

Wang, Zhen, Zhang, Jifeng, Li, Hong, Li, Junyi, Niimi, Manabu, Ding, Guohui, Chen, Haifeng, Xu, Jie, Zhang, Hongjiu, Xu, Ze, Dai, Yulin, Gui, Tuantuan, Li, Shengdi, Liu, Zhi, Wu, Sujuan, Cao, Mushui, Zhou, Lu, Lu, Xingyu, Wang, Junxia, Yang, Jing, Fu, Yunhe, Yang, Dongshan, Song, Jun, Zhu, Tianqing, Li, Shen, Ning, Bo, Wang, Ziyun, Koike, Tomonari, Shiomi, Masashi, Liu, Enqi, Chen, Luonan, Fan, Jianglin, Chen, Y. Eugene, and Li, Yixue

Published
2016
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43. Screening of Candidate Pathogenic Genes for Spontaneous Abortion Using Whole Exome Sequencing

Author

Tao Zhou, Li Chen, Qingwen Zhu, Jiayi Ding, Wenjun Bian, Ding Guohui, Li Guang, Yiwen Zhou, and Liu Jia

Subjects
Genetics, Mutation, Organic Chemistry, High-Throughput Nucleotide Sequencing, Single-nucleotide polymorphism, General Medicine, Gene mutation, Biology, medicine.disease_cause, Genome, Polymorphism, Single Nucleotide, Computer Science Applications, Abortion, Spontaneous, Pregnancy, Drug Discovery, Exome Sequencing, medicine, Humans, Female, KEGG, Indel, Gene, Exome sequencing
Abstract

Background: Spontaneous abortion is a common disease in obstetrics and reproduction. Objective: This study aimed to screen candidate pathogenic genes for spontaneous abortion using whole-exome sequencing. Methods: Genomic DNA was extracted from abortion tissues of spontaneous abortion patients and sequenced using the Illumina HiSeq2500 high-throughput sequencing platform. Whole exome sequencing was performed to select harmful mutations, including SNP and insertion and deletion sites, associated with spontaneous abortion. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene fusion analyses were performed. MUC3A and PDE4DIP were two novel mutation genes that were screened and verified by PCR in abortion tissues of patients. Results: A total of 83,633 SNPs and 13,635 Indel mutations were detected, of which 29172 SNPs and 3093 Indels were screened as harmful mutations. The 7 GO-BP, 4 GO-CC, 9 GO-MF progress, and 3 KEGG pathways were enriched in GO and KEGG pathway analyses. A total of 746 gene fusion mutations were obtained, involving 492 genes. MUC3A and PDE4DIP were used for PCR verification because of their high number of mutation sites in all samples. Conclusion: There are extensive SNPs and Indel mutations in the genome of spontaneous abortion tissues, and the effect of these gene mutations on spontaneous abortion needs further experimental verification.

Published
2021

46. Subtyping of type A influenza by sequencing the variable regions of HA gene specifically amplified with RT-PCR

Author

Yan, An, Ding, GuoHui, Zhou, ZhenFeng, Dong, Hui, Zhang, YaKun, Zhu, Lei, He, YunGang, Zhang, GuoQing, Li, YiXue, Sun, Bing, Huang, Zhong, Lan, Ke, Jin, Li, Wang, HongYan, Wang, XiaoNing, Yang, Zhong, Zhong, Yang, Dai, JianXin, Guo, YaJun, Wang, Hao, Che, XiaoYan, Wu, Fan, Yuan, ZhenGan, Zhang, Xi, Cao, ZhiWei, Zhou, XiaoNong, Zhou, JiaHai, Ma, ZhiYong, Tong, GuangZhi, Zhao, GuoPing, Jin, WeiRong, and Xiong, Hui

Published
2009
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48. Detecting the borders between coding and non-coding DNA regions in prokaryotes based on recursive segmentation and nucleotide doublets statistics

Author

Deng Suping, Shi Yixiang, Yuan Liyun, Li Yixue, and Ding Guohui

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Detecting the borders between coding and non-coding regions is an essential step in the genome annotation. And information entropy measures are useful for describing the signals in genome sequence. However, the accuracies of previous methods of finding borders based on entropy segmentation method still need to be improved. Methods In this study, we first applied a new recursive entropic segmentation method on DNA sequences to get preliminary significant cuts. A 22-symbol alphabet is used to capture the differential composition of nucleotide doublets and stop codon patterns along three phases in both DNA strands. This process requires no prior training datasets. Results Comparing with the previous segmentation methods, the experimental results on three bacteria genomes, Rickettsia prowazekii, Borrelia burgdorferi and E.coli, show that our approach improves the accuracy for finding the borders between coding and non-coding regions in DNA sequences. Conclusions This paper presents a new segmentation method in prokaryotes based on Jensen-Rényi divergence with a 22-symbol alphabet. For three bacteria genomes, comparing to A12_JR method, our method raised the accuracy of finding the borders between protein coding and non-coding regions in DNA sequences.

Published
2012
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49. Genome assembly and transcriptome analysis provide insights into the antischistosome mechanism of Microtus fortis

Author

Li, Hong, primary, Wang, Zhen, additional, Chai, Shumei, additional, Bai, Xiong, additional, Ding, Guohui, additional, Li, Yuanyuan, additional, Li, Junyi, additional, Xiao, Qingyu, additional, Miao, Benpeng, additional, Lin, Weili, additional, Feng, Jie, additional, Huang, Mingyue, additional, Gao, Cheng, additional, Li, Bin, additional, Hu, Wei, additional, Lin, Jiaojiao, additional, Fu, Zhiqiang, additional, Xie, Jianyun, additional, and Li, Yixue, additional

Published
2020
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