Article
Biochemical Research Methods
Buwen Cao, Shuguang Deng, Hua Qin, Jiawei Luo, Guanghui Li, Cheng Liang
Summary: This study successfully inferred miRNA-disease relationships by constructing a miRNA functional similarity network and utilizing an improved K-means algorithm. Experimental results demonstrated that the performance of IK-means algorithm was superior to classical K-means algorithms in identifying new miRNA-disease associations.
JOURNAL OF COMPUTATIONAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Alexandros Armaos, Alessio Colantoni, Gabriele Proietti, Jakob Rupert, Gian Gaetano Tartaglia
Summary: The catRAPID omics v2.0 web server is a powerful tool for characterizing and classifying RNA-protein interactions. It allows for the prediction of interactions between custom protein sets and RNA sets, as well as the analysis of long linear RNAs and circular RNAs.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemical Research Methods
ShuDong Wang, YunYin Li, YuanYuan Zhang, ShanChen Pang, SiBo Qiao, Yu Zhang, FuYu Wang
Summary: Numerous biological studies have shown that disease-associated microRNAs (miRNAs) can be used as biomarkers or therapeutic targets for diagnosing complex diseases. In this study, we propose a computational model called GAMCNMDF which integrates diverse data sources and employs a nonlinear fusion approach to predict miRNA-disease associations. The model creates a diverse network connecting miRNAs and diseases, represented as a matrix, and uses a generative adversarial matrix completion network to predict the associations.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Genetics & Heredity
Min Chen, Yingwei Deng, Ang Li, Yan Tan
Summary: This article presents an integrated method called LPARP, based on label-propagation algorithm and random projection, for predicting lncRNA-disease associations. Empirical experiments show that LPARP outperforms existing methods and is validated in case studies of various diseases. LPARP can serve as an effective and reliable tool for biomedical research.
FRONTIERS IN GENETICS
(2022)
Article
Biochemical Research Methods
Qingfeng Chen, Dehuan Lai, Wei Lan, Ximin Wu, Baoshan Chen, Jin Liu, Yi-Ping Phoebe Chen, Jianxin Wang
Summary: This article introduces a novel framework ILDMSF that combines lncRNA similarities and disease similarities for predicting potential lncRNA-disease relationships, utilizing support vector machine for identification and conducting leave-one-out cross validation to compare with other methods, showing prospective results in exploring correlations between lncRNA and disease.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Liang Shu, Cheng Zhou, Xinxu Yuan, Jingpu Zhang, Lei Deng
Summary: The study introduces a new method MSCFS for calculating the functional similarity of circRNA by integrating multiple data sources. Utilizing different learning representation methods to establish circRNA functional similarity networks and evaluating the method's performance using circRNA-miRNA association and co-expression similarity.
BMC BIOINFORMATICS
(2021)
Review
Biochemical Research Methods
Maryam Mahjoubin-Tehran, Samaneh Rezaei, Amin Jalili, Amirhossein Sahebkar, Seyed Hamid Aghaee-Bakhtiari
Summary: MicroRNAs play a crucial role in regulating gene expression and signaling pathways, making them important regulators in cellular processes and diseases. Understanding the relationship between miRNAs and diseases is of great interest in research, and databases offer valuable information for identifying critical miRNAs and their clinical applications. This review summarizes miRNAs-disease databases and their limitations, providing researchers with a comprehensive reference and developers/designers with a guideline for database features and limitations.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Wen Zhang, Zhishuai Li, Wenzheng Guo, Weitai Yang, Feng Huang
Summary: The paper introduces a network link inference method FLNSNLI based on linear neighborhood similarity for predicting miRNA-disease associations, which shows high accuracy and outperforms other methods. It performs well in predicting links for miRNAs or diseases without known associations.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Biotechnology & Applied Microbiology
Junliang Shang, Yi Yang, Feng Li, Boxin Guan, Jin-Xing Liu, Yan Sun
Summary: This study proposes a method called BLNIMDA based on a weighted bi-level network for predicting hidden associations between miRNAs and diseases. The method defines different types of miRNA-disease associations and introduces affinity weights evaluation from bidirectional information distribution strategy and defined association types, ensuring comprehensive and accurate prediction of miRNA-disease associations. The results show that BLNIMDA outperforms other computational methods in terms of predictive performance.
Article
Biochemistry & Molecular Biology
Brad T. Sherman, Ming Hao, Ju Qiu, Xiaoli Jiao, Michael W. Baseler, H. Clifford Lane, Tomozumi Imamichi, Weizhong Chang
Summary: DAVID, a popular bioinformatics resource system, has undergone updates in 2021, including the rebuilding of the DAVID Gene system, increasing the number of gene-term records for annotation types, adding new annotations, assigning specific subgroups, and adding a species parameter for improved user experience.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Chemistry, Medicinal
Shahid Iqbal, Fang Ge, Fuyi Li, Tatsuya Akutsu, Yuanting Zheng, Robin B. Gasser, Dong-Jun Yu, Geoffrey Webb, Jiangning Song
Summary: PROST is a sequence-based predictor for protein stability changes caused by single-point missense mutations. It utilizes various sequence-based features, physicochemical properties, evolutionary information, and predicted structural features to accurately predict the protein stability changes. The performance of PROST is evaluated on multiple datasets and compared with state-of-the-art predictors, demonstrating its superiority.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Biochemical Research Methods
Joshua M. Toth, Paul J. DePietro, Juergen Haas, William A. McLaughlin
Summary: The ResiRole method is used to assess the quality of protein structure models, ranking structure prediction techniques based on round-robin comparisons using difference scores. These difference scores show strong correlation with other model quality metrics and are able to detect additional local structural similarities between the structure models and reference structures.
Article
Medicine, Research & Experimental
Young Joo Sun, Gabriel Velez, Dylan E. Parsons, Kun Li, Miguel E. Ortiz, Shaunik Sharma, Paul B. McCray, Alexander G. Bassuk, Vinit B. Mahajan
Summary: This study identified structurally similar serine proteases to TMPRSS2 using a structure-based computational tool and demonstrated several candidate compounds that effectively inhibit SARS-CoV-2 infection. Avoralstat, a clinically tested inhibitor, showed potential in decreasing viral load and mitigating infection-induced damage, suggesting its repositioning for COVID-19 prophylaxis.
JOURNAL OF CLINICAL INVESTIGATION
(2021)
Article
Microbiology
Lieqing Lin, Ruibin Chen, Yinting Zhu, Weijie Xie, Huaiguo Jing, Langcheng Chen, Minqing Zou
Summary: Accumulating evidence has shown that long non-coding RNAs (lncRNAs) are associated with human diseases, including abnormal expression caused by microbial influences. Understanding lncRNA-disease associations is crucial for disease diagnosis, treatment, and prevention. To address the limitations in current prediction methods, a correction-based similarity-constrained probability matrix decomposition method (SCCPMD) is proposed, which leverages microbial associations and similarity information to accurately predict potential lncRNA-disease associations. Experimental results demonstrate that SCCPMD outperforms other algorithms, with high prediction accuracy in case studies of breast cancer, lung cancer, and renal cell carcinoma.
FRONTIERS IN MICROBIOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Yanbu Guo, Dongming Zhou, Xiaoli Ruan, Jinde Cao
Summary: The study presents a feature extraction model based on variational gated autoencoder for inferring potential disease-miRNA associations. Experimental results show that the proposed model achieves remarkable association prediction performance, validating the efficacy of the variational gate mechanism and contrastive cross-entropy loss for inferring disease-miRNA associations.
Article
Multidisciplinary Sciences
Yuequan Zhu, Kai Xiong, Jiangcheng Shi, Qinghua Cui, Lixiang Xue
Article
Genetics & Heredity
Chunmei Cui, Weili Yang, Jiangcheng Shi, Yong Zhou, Jichun Yang, Qinghua Cui, Yuan Zhou
GENOMICS PROTEOMICS & BIOINFORMATICS
(2018)
Article
Biochemistry & Molecular Biology
Zhou Huang, Jiangcheng Shi, Yuanxu Gao, Chunmei Cui, Shan Zhang, Jianwei Li, Yuan Zhou, Qinghua Cui
NUCLEIC ACIDS RESEARCH
(2019)
Article
Genetics & Heredity
Yuanxu Gao, Kaiwen Jia, Jiangcheng Shi, Yuan Zhou, Qinghua Cui
FRONTIERS IN GENETICS
(2019)
Article
Cardiac & Cardiovascular Systems
Peng Hui, Yang Bai, Xing Su, Nanhu Quan, Bokang Qiao, Yang Zheng, Jiangcheng Shi, Xiaoyu Du, Jie Lu
INTERNATIONAL JOURNAL OF CARDIOLOGY
(2020)
Article
Mathematical & Computational Biology
Kaiwen Jia, Yuanxu Gao, Jiangcheng Shi, Yuan Zhou, Yong Zhou, Qinghua Cui
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2020)
Article
Medicine, Research & Experimental
Jiangcheng Shi, Qinghua Cui
MOLECULAR THERAPY-NUCLEIC ACIDS
(2020)
Article
Medicine, Research & Experimental
Jiangcheng Shi, Chengqing Hu, Yuan Zhou, Chunmei Cui, Jichun Yang, Qinghua Cui
MOLECULAR THERAPY-NUCLEIC ACIDS
(2020)
Article
Biology
Chengqing Hu, Jiangcheng Shi, Yujing Chi, Jichun Yang, Qinghua Cui
Summary: The study reveals that X-chromosome-encoded miRNAs have lower expression levels in the left testis of healthy mice, suggesting an imbalanced Y:X ratio between the left and right testis. Additionally, the Y:X ratio is significantly elevated in the left testis but balanced in the right testis according to flow cytometry analysis. This is the first time the biased Y:X ratio in the left testis has been uncovered.
Article
Biochemistry & Molecular Biology
Yu Deng, He Huang, Jiangcheng Shi, Hongyan Jin
Summary: This study identified several genes, including CCNE2, that may play a role in MHT-related breast cancer development. CCNE2 may serve as a sensitive risk indicator for breast cancer in women using MHT.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biotechnology & Applied Microbiology
Zhou Huang, Leibo Liu, Yuanxu Gao, Jiangcheng Shi, Qinghua Cui, Jianwei Li, Yuan Zhou
