Article
Biochemistry & Molecular Biology
Hao Tian, Rajas Ketkar, Peng Tao
Summary: The work presents an accurate ADMET prediction model using an ensemble of features and a tree-based machine learning model. The model performs well in the ADMET benchmark test and is ranked top 3 in most tasks. The trained machine learning models are integrated in a publicly available web server named ADMET boost.
JOURNAL OF MOLECULAR MODELING
(2022)
Article
Biochemistry & Molecular Biology
Lukasz Pawel Kozlowski
Summary: The isoelectric point is the pH at which a molecule is electrically neutral, dependent on factors like charged groups from amino acids in proteins and peptides, and is used in experiments like 2D gel electrophoresis and computational predictions. IPC 2.0, utilizing a mix of deep learning and support vector regression models, outperforms previous algorithms in predicting proteins and peptides' isoelectric points with higher accuracy. Additionally, the web server's prediction of pK(a) values using sequence data alone is better and faster than structure-based methods.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Yuexu Jiang, Lei Jiang, Chopparapu Sai Akhil, Duolin Wang, Ziyang Zhang, Weinan Zhang, Dong Xu
Summary: The study introduces a new web application based on MULocDeep, which has improved performance, result interpretation, and visualization, for predicting protein localization and understanding its mechanisms. By transferring the original model into species-specific models, MULocDeep achieves competitive prediction performance at the subcellular level compared to other state-of-the-art methods. Besides localization prediction, the web service quantifies the contribution of single amino acids to localization for individual proteins and derives common motifs or potential targeting-related regions for a group of proteins. The visualizations of targeting mechanism analyses can be downloaded for publication-ready figures. The MULocDeep web service is available at https://www.mu-loc.org/.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Computer Science, Information Systems
Yatao Yang, Zibin Zheng, Xiangdong Niu, Mingdong Tang, Yutong Lu, Xiangke Liao
Summary: With the prevalence of web services, selecting the optimal service among similar candidates relies on the Quality of Service (QoS). To enhance prediction accuracy of QoS values, a novel method based on factorization machine has been proposed, leveraging both user and service information for prediction.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Biochemistry & Molecular Biology
Wanshan Ning, Yuxiang Wei, Letian Gao, Cheng Han, Yujie Gou, Shanshan Fu, Dan Liu, Chi Zhang, Xinhe Huang, Sicheng Wu, Di Peng, Chenwei Wang, Yu Xue
Summary: This article introduces the features and advantages of Heml 2.0 software, which can be used for visualization of biomolecular expression data and enrichment analysis. Heml 2.0 offers various clustering methods and distance metrics, and provides multiple export and visualization options, offering users convenient and comprehensive analysis tools.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Roaa ElGhondakly, Sherin M. Moussa, Nagwa Badr
Summary: As service-oriented computing systems become more complex, fault prediction plays a crucial role in reducing testing cost and increasing the reliability of service compositions. This paper proposes a multilateral fault prediction and localization approach using deep learning techniques for web service compositions testing. The approach not only predicts faulty services, but also their count and severity, location of faults, and time of occurrence. Experimental analysis shows that the hybrid CNN_RNN model achieves higher accuracy and lower mean square error compared to the individual CNN and RNN models.
APPLIED SOFT COMPUTING
(2023)
Article
Biochemistry & Molecular Biology
Minh N. Nguyen, Nora L. Krutz, Vachiranee Limviphuvadh, Andreas L. Lopata, G. Frank Gerberick, Sebastian Maurer-Stroh
Summary: AllerCatPro 2.0 is a web server for predicting the allergenic potential of proteins with better accuracy than other methods, and new features to help assessors make informed decisions. It predicts protein similarity using amino acid sequences and predicted 3D structures.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Computer Science, Information Systems
Boxiong Tan, Hui Ma, Yi Mei, Mengjie Zhang
Summary: As the number of functionally similar web services on the Internet continues to increase, market competition has become intense. Web service providers recognize that good Quality of Service (QoS) is crucial for business success, with low network latency being a key indicator of good QoS. This paper addresses the challenges of the Web Service Location Allocation Problem (WSLAP) by developing a new PSO-based algorithm that can provide a wider range of solutions compared to existing multi-objective optimization algorithms, particularly performing better on larger scale problems.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2021)
Article
Computer Science, Information Systems
Seyyed Hamid Ghafouri, Seyyed Mohsen Hashemi, Patrick C. K. Hung
Summary: This article discusses methods for predicting QoS values of web services and recommending the best services based on these values. The methods are categorized into memory-based, model-based, and collaborative filtering methods combined with other techniques. The article introduces famous studies in each category, reviews the problems and benefits of each category, and proposes suggestions for future work.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Information Systems
Zibin Zheng, Xiaoli Li, Mingdong Tang, Fenfang Xie, Michael R. Lyu
Summary: With the increase in competing web services, quality-of-service (QoS) prediction becomes important for QoS-aware approaches. Collaborative filtering (CF) is a successful personalized prediction technique that has been widely used in web service QoS prediction. In addition to conventional CF techniques, studies have extended CF by incorporating additional information about services and users. This survey summarizes and analyzes the state-of-the-art CF QoS prediction approaches, discusses their features and differences, and presents benchmark datasets for evaluating prediction accuracy and future research directions.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Chemistry, Multidisciplinary
Jiarui Chen, Yain-Whar Si, Chon-Wai Un, Shirley W. Siu
Summary: This study introduces a Graph Convolution Neural Network (GCN) model for predicting chemical toxicity, trained using the Mean Teacher (MT) semi-supervised learning algorithm. The model achieves better performance compared to traditional supervised learning and machine learning methods, demonstrating the potential of learning from unannotated data to enhance predictive power.
JOURNAL OF CHEMINFORMATICS
(2021)
Article
Computer Science, Information Systems
Min Shi, Yuan Zhuang, Yufei Tang, Maohua Lin, Xingquan Zhu, Jianxun Liu
Summary: This article focuses on the problem of Web service network embedding, aiming to learn low-dimensional vectors to represent services by encoding both Mashup-API composition structure and service functional content. By proposing a novel probabilistic topic model and a Service Graph Convolutional Network (Service-GCN), the method achieves improvements in downstream classification and clustering tasks. Experimental results show that the proposed approach outperforms the state-of-the-art methods in service classification and Mashup clustering.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Biochemistry & Molecular Biology
Xinkang Li, Lijun Tang, Zeying Li, Dian Qiu, Zhuoling Yang, Baoqiong Li
Summary: In this study, machine learning algorithms including PLS-DA, AdaBoost, and LGBM were applied to establish models for predicting the ADMET properties of anti-breast cancer compounds. The LGBM algorithm yielded the best results compared to the other two algorithms, with high accuracy, precision, recall, and F1-score. The findings suggest that LGBM can be a reliable tool for predicting molecular ADMET properties in virtual screening and drug design research.
Article
Mathematics, Applied
Fadl Dahan
Summary: In this study, an Improved Whale Optimization Algorithm (IWOA) is proposed to enhance the performance of the Web Service Composition (WSC) problem. The IWOA introduces different strategies, including the Sine chaos theory, Levy flight mechanism, and neighborhood search mechanism, to improve the convergence speed and solution accuracy of the WSC problem. Experimental results show that the IWOA outperforms the standard WOA and other swarm-based algorithms in terms of fitness values, with a trade-off in execution time.
Article
Computer Science, Hardware & Architecture
Yang Song
Summary: This paper introduces a new web service reliability prediction method based on machine learning, which can solve the data sparsity problem and improve accurate web service reliability prediction. The method combines user, service, and web condition parameters to predict the reliability of web services by aggregating data and constructing a feedback matrix.
COMPUTER STANDARDS & INTERFACES
(2021)
Article
Chemistry, Medicinal
Yingchun Cai, Hongbin Yang, Weihua Li, Guixia Liu, Philip W. Lee, Yun Tang
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2018)
Article
Chemistry, Medicinal
Zhuang Wang, Hongbin Yang, Zengrui Wu, Tianduanyi Wang, Weihua Li, Yun Tang, Guixia Liu
Article
Chemistry, Medicinal
Hongbin Yang, Lixia Sun, Zhuang Wang, Weihua Li, Guixia Liu, Yun Tang
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2018)
Article
Chemistry, Medicinal
Yingchun Cai, Hongbin Yang, Weihua Li, Guixia Liu, Philip W. Lee, Yun Tang
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2019)
Article
Toxicology
Changsheng Jiang, Hongbin Yang, Peiwen Di, Weihua Li, Yun Tang, Guixia Liu
JOURNAL OF APPLIED TOXICOLOGY
(2019)
Article
Chemistry, Medicinal
Lixia Sun, Hongbin Yang, Yingchun Cai, Weihua Li, Guixia Liu, Yun Tang
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2019)
Article
Environmental Sciences
Lujue He, Keya Xiao, Cong Zhou, Guanglong Li, Hongbin Yang, Zhong Li, Jiagao Cheng
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2019)
Article
Toxicology
Peiwen Di, Zengrui Wu, Hongbin Yang, Weihua Li, Yun Tang, Guixia Liu
TOXICOLOGY LETTERS
(2019)
Article
Toxicology
Yayuan Peng, Zengrui Wu, Hongbin Yang, Yingchun Cai, Guixia Liu, Weihua Li, Yun Tang
TOXICOLOGY LETTERS
(2019)
Article
Toxicology
Lin Liu, Hongbin Yang, Yingchun Cai, Qianqian Cao, Lixia Sun, Zhuang Wang, Weihua Li, Guixia Liu, Philip W. Lee, Yun Tang
TOXICOLOGY RESEARCH
(2019)
Article
Biochemistry & Molecular Biology
Longfei Guan, Hongbin Yang, Yingchun Cai, Lixia Sun, Peiwen Di, Weihua Li, Guixia Liu, Yun Tang
Article
Chemistry, Medicinal
Lixia Sun, Hongbin Yang, Jie Li, Tianduanyi Wang, Weihua Li, Guixia Liu, Yun Tang
