Article
Biochemistry & Molecular Biology
Andi Nur Nilamyani, Firda Nurul Auliah, Mohammad Ali Moni, Watshara Shoombuatong, Md Mehedi Hasan, Hiroyuki Kurata
Summary: Nitrotyrosine, a type of protein post-translational modification, is generated by reactive nitrogen species. Computational prediction, such as the PredNTS predictor developed in this study, plays a vital role in understanding nitrated proteins before biological experimentation. The PredNTS predictor outperforms existing predictors and provides a useful computational resource for predicting nitrotyrosine sites.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Computer Science, Information Systems
Deli Xu, Yafei Zhu, Qiang Xu, Yuhai Liu, Yu Chen, Yang Zou, Lei Li
Summary: In this study, a predictor called DTL-NeddSite was developed using deep transfer learning strategy, which significantly improved the prediction performance and is crucial for understanding the mechanisms of protein neddylation.
Article
Biochemical Research Methods
Priya Gupta, Sureshkumar Venkadesan, Debasisa Mohanty
Summary: Despite the lack of available software for predicting phosphosites for Plasmodium proteins, this study presents Pf-Phospho, a machine learning-based method for accurate prediction of phosphorylation sites in Plasmodium. Pf-Phospho outperforms other widely used prediction tools and integrates with popular resources for comprehensive analysis of phospho-signaling networks in Plasmodium.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Md Sohrawordi, Md Ali Hossain, Md Al Mehedi Hasan
Summary: This article introduces a newly invented post-translational modification (PTM) called phosphoglycerylation, which plays an essential role in protein construction, functional properties, and human diseases. The authors designed an effective predictor named PLP_FS to accurately identify phosphoglycerylation sites, achieving higher accuracy, sensitivity, and specificity compared to other existing predictors.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Zhe Ju, Shi-Yun Wang
Summary: A novel bioinformatics tool named HMGPred was developed to predict HMGylation sites in this study. Multiple effective features were integrated to encode HMGylation sites, and feature selection was performed to eliminate redundant features. The fuzzy support vector machine algorithm was used to reduce the influence of noise problem. HMGPred achieved satisfactory performance with an area under receiver operating characteristic curve of 0.9110 according to 10-fold cross-validation.
ANALYTICAL BIOCHEMISTRY
(2023)
Review
Biochemistry & Molecular Biology
A. El Allali, Zahra Elhamraoui, Rachid Daoud
Summary: This review explores machine learning approaches used for predicting 11 RNA modification types, covering the life cycle of predicting RNA modification sites. Methods are compared in terms of datasets, target species, approach, and accuracy for each RNA modification type, with advantages, limitations, and future perspectives also discussed. Machine learning has shown promise in predicting RNA modifications, but further research and development are needed to improve accuracy and application.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Genetics & Heredity
Xiao Yang, Xiucai Ye, Xuehong Li, Lesong Wei
Summary: This study proposed a computational method, iDNA-MT, to identify 4mC sites and 6mA sites in multiple species. Experimental results show that iDNA-MT outperforms other state-of-the-art single-task methods for identifying 4mA or 6mC sites in multiple species. The promising results demonstrate that iDNA-MT has great potential to be a powerful and practically useful tool for accurately identifying DNA modifications.
FRONTIERS IN GENETICS
(2021)
Article
Chemistry, Multidisciplinary
Ban Fei, Chaoqi Zhang, Daoping Cai, Jingying Zheng, Qidi Chen, Yulan Xie, Longzhen Zhu, Andreu Cabot, Hongbing Zhan
Summary: Developing high-performance cathode host materials is crucial for solving the issues of low sulfur utilization, sluggish redox kinetics, and LiPS shuttle effect in lithium-sulfur batteries. The multifunctional Ag/VN@Co/NCNT nanocomposite with hierarchical nano-reactors shows outstanding electrochemical performances, bringing lithium-sulfur batteries closer to practical application.
Article
Biochemical Research Methods
Yingxi Yang, Hui Wang, Wen Li, Xiaobo Wang, Shizhao Wei, Yulong Liu, Yan Xu
Summary: The MultiLyGAN machine learning pipeline showed good predictive performance for identifying lysine modified sites in proteins, with CWGAN being effective in addressing data imbalance. CKSAAP, PWM, and structural features were identified as the most important feature-encoding schemes.
BMC BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Sharaf J. Malebary, Ebraheem Alzahrani, Yaser Daanial Khan
Summary: This study aims to accurately predict glutamine sites vulnerable to methylation using computationally intelligent classifiers, with deep learning performing best among them.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2022)
Article
Multidisciplinary Sciences
Enyu Wu, Xiao-Wen Gu, Di Liu, Xu Zhang, Hui Wu, Wei Zhou, Guodong Qian, Bin Li
Summary: This study reports a strategy of constructing multiple supramolecular binding sites in a MOF for efficient one-step purification of C2H4 from ternary mixtures. The material exhibits high adsorption capacity and selectivity, and can be easily prepared using a green synthesis method and scaled up for industrial production.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Xue-Ling Chen, Mo Xie, Ze-Lin Zheng, Xiao Luo, Hongchang Jin, Yan-Fei Chen, Guo-Zhan Yang, De-Shan Bin, Dan Li
Summary: Based on theoretical calculations, a porous bulk covalent organic framework (COF) with numerous pyrazines and carbonyls is found to provide multiple redox-active sites for high-performance potassium storage. Its porous structure and surface-dominated storage mechanism enable fast and stable storage of K-ions. As a potassium-ion battery anode, this COF exhibits excellent reversible capacity, rate capability, and cyclability due to its unique properties.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Biochemical Research Methods
Yong-Zi Chen, Zhuo-Zhi Wang, Yanan Wang, Guoguang Ying, Zhen Chen, Jiangning Song
Summary: Lysine crotonylation (Kcr) has been reported to be involved in various pathophysiological processes, and several predictors have been developed for predicting Kcr sites, most of which are only suitable for histones or a mix of histone and nonhistone proteins. The proposed CNNrgb framework shows the best performance in predicting Kcr sites on nonhistone proteins and exhibits high computational efficiency.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Haodong Xu, Peilin Jia, Zhongming Zhao
Summary: This study reviewed the computational prediction of 4mC sites and developed Deep4mC, a deep learning-based model, which showed high accuracy and robust performance in predicting putative 4mC sites in genomes of various species. With feature optimization and reinforcement learning, Deep4mC achieved significant improvement in performance compared to previous tools.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Physical
Chaoqi Zhang, Ruifeng Du, Jordi Jacas Biendicho, Mingjie Yi, Ke Xiao, Dawei Yang, Ting Zhang, Xiang Wang, Jordi Arbiol, Jordi Llorca, Yingtang Zhou, Joan Ramon Morante, Andreu Cabot
Summary: A Mott-Schottky catalyst based on bimetallic phosphide CoFeP nanocrystals supported on carbon nitride tubular nanostructures is proposed to enhance the performance of lithium-sulfur batteries. The CoFeP@CN composites demonstrated superior rate performance and cycling stability, effectively addressing the issues often overlooked in LSBs.
ADVANCED ENERGY MATERIALS
(2021)
Article
Multidisciplinary Sciences
Qi Zhao, Feng Wang, Yan-Xing Chen, Shifu Chen, Yi-Chen Yao, Zhao-Lei Zeng, Teng-Jia Jiang, Ying-Nan Wang, Chen-Yi Wu, Ying Jing, You-Sheng Huang, Jing Zhang, Zi-Xian Wang, Ming-Ming He, Heng-Ying Pu, Zong-Jiong Mai, Qi-Nian Wu, Renwen Long, Xiaoni Zhang, Tanxiao Huang, Mingyan Xu, Miao-Zheng Qiu, Hui-Yan Luo, Yu-Hong Li, Dong-Shen Zhang, Wei-Hua Jia, Gong Chen, Pei-Rong Ding, Li-Ren Li, Zheng-Hai Lu, Zhi-Zhong Pan, Rui-Hua Xu
Summary: Through ultradeep whole-exome sequencing, we identified 46 significantly mutated genes associated with CRC and proposed a subtyping strategy that classifies CRC patients into four genomic subtypes with distinct clinical characteristics. Additionally, we found that mitochondrial DNA copy number is an independent factor for predicting the survival outcome of CRCs.
NATURE COMMUNICATIONS
(2022)
Article
Genetics & Heredity
Zhen Zhang, Zi-Xian Wang, Yan-Xing Chen, Hao-Xiang Wu, Ling Yin, Qi Zhao, Hui-Yan Luo, Zhao-Lei Zeng, Miao-Zhen Qiu, Rui-Hua Xu
Summary: By analyzing single-cell RNA sequencing data from ICI-treated patients, it was found that cancer stemness may be associated with resistance to ICI treatment. The developed novel stemness signature (Stem.Sig) showed improved predictive performance for ICI response across multiple cancers, potentially serving as a competitive tool for patient selection in immunotherapy.
Review
Biotechnology & Applied Microbiology
Kunxiang Liu, Qi Zhao, Bei Li, Xia Zhao
Summary: This article reviews the applications of Raman spectroscopy for in vivo and in vitro diagnosis of gastric cancer, methodology related to spectroscopy data analysis, and presents the limitations of the technique.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Oncology
Jingjing Qi, Di Cui, Qi-Nian Wu, Qi Zhao, Zhan-Hong Chen, Lianjie Li, Walter Birchmeier, Yong Yu, Ran Tao
Summary: Metastasis, EMT and CSC are critically regulated by DNA methylation and Wnt/beta-catenin signaling in gastric cancer. This study identifies a TET1-FOXO4-beta-catenin signaling cascade that inhibits beta-catenin activity and nuclear translocation, leading to suppression of EMT and stemness properties of gastric cancer cells. Knocking-down TET1 enhances metastasis and self-renewal of CSCs through activating Wnt signaling, which can be rescued by modulating FOXO4 expression. Low expression of TET1 or FOXO4 predicts poor survival of gastric cancer patients, suggesting TET1 or FOXO4 reactivation as a potential therapeutic approach for preventing gastric cancer metastasis.
Article
Biochemistry & Molecular Biology
Wen-Kang Shen, Si-Yi Chen, Zi-Quan Gan, Yu-Zhu Zhang, Tao Yue, Miao-Miao Chen, Yu Xue, Hui Hu, An-Yuan Guo
Summary: Transcription factors (TFs) are proteins that interact with specific DNA sequences to regulate gene expression. The Animal Transcription Factor Database (AnimalTFDB) has been updated to version 4.0 with new data and functions, including variations in TF genes in human cancers and other diseases, predicted post-translational modification sites on TFs, TF regulation in autophagy, comprehensive TF expression annotation, and improved search functions.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Kai Yu, Ye Wang, Yongqiang Zheng, Zekun Liu, Qingfeng Zhang, Siyu Wang, Qi Zhao, Xiaolong Zhang, Xiaoxing Li, Rui-Hua Xu, Ze-Xian Liu
Summary: Post-translational modifications (PTMs) play critical roles in regulating protein functions and understanding biological processes and diseases. The qPTM database serves as a comprehensive one-stop data resource, providing massive quantitative PTM proteome datasets and a scoring system to assess PTM site reliability.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Xiaoqiong Bao, Yin Zhang, Huiqin Li, Yuyan Teng, Lixia Ma, Zhihang Chen, Xiaotong Luo, Jian Zheng, An Zhao, Jian Ren, Zhixiang Zuo
Summary: RNA modification is a dynamic and reversible process regulated by writers, erasers and readers (WERs). Abnormal changes of WERs disrupt RNA modification homeostasis, leading to dysregulation of RNA metabolism and diseases. The RM2Target database stores WER-target associations for nine RNA modifications, providing extensive annotations for target genes and facilitating downstream functional and mechanistic studies in RNA modification research.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Kai Yu, Zekun Liu, Haoyang Cheng, Shihua Li, Qingfeng Zhang, Jia Liu, Huai-Qiang Ju, Zhixiang Zuo, Qi Zhao, Shiyang Kang, Ze-Xian Liu
Summary: This study presents a novel software, dSCOPE, for predicting protein sequence segments critical for liquid-liquid phase separation (LLPS). The large-scale analysis of the human proteome based on dSCOPE reveals potential roles and associations with post-translational modifications, cancer mutations, and cellular signaling pathways.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Oncology
Zeyu Yan, Qing Yuan, Yiwei He, Fan Peng, Yang Liu, Huanqin Zhang, Xiaoying Ji, Xianli He, Qi Zhao, Jinliang Xing, Xu Guo
Summary: The mtDNA haplogroup M7 was found to be associated with the prognosis of Chinese colorectal cancer patients. A M7-based mtSNP classifier was developed and showed potential for predicting the prognosis of colorectal cancer patients, providing a tool for clinical decision-making. RNA-seq and immunohistochemical analyses suggested that the poor prognosis of patients with haplogroup M7 may be related to mitochondrial dysfunction and immune abnormalities.
Article
Gastroenterology & Hepatology
Shuling Chen, Cheng Huang, Guanrui Liao, Huichuan Sun, Yubin Xie, Changyi Liao, Jianping Wang, Minghui He, Huanjing Hu, Zihao Dai, Xiaoxue Ren, Xuezhen Zeng, Zhilong Lin, Guo-Pei Zhang, Wenxuan Xie, Shunli Shen, Shaoqiang Li, Sui Peng, Dong-Ming Kuang, Qiang Zhao, Dan G. Duda, Ming Kuang
Summary: Analyzing the single-cell immune ecosystems in recurrent hepatocellular carcinoma (HCC) can aid in the development of effective immunotherapies. The study identified de novo and true recurrences in HCC samples and found distinct immune characteristics in the tumor immune microenvironment (TIME) of these recurrences. The findings suggest the need for different immunotherapy strategies based on the type of HCC recurrence and the specific TIME.
Article
Biochemistry & Molecular Biology
Jiaqi Liang, Chaoye Wang, Di Zhang, Yubin Xie, Yanru Zeng, Tianqin Li, Zhixiang Zuo, Jian Ren, Qi Zhao
Summary: This article introduces a method called VSOLassoBag, which integrates an ensemble learning strategy to select efficient and stable variables from high-dimensional biological data for biomarker determination. The application of VSOLassoBag on simulation and real-world datasets shows its effectiveness in identifying markers for binary classification and prognosis prediction, with comparable performance and fewer features compared to other algorithms.
JOURNAL OF GENETICS AND GENOMICS
(2023)
Article
Biochemistry & Molecular Biology
Yongbiao Xue, Yiming Bao, Zhang Zhang, Wenming Zhao, Jingfa Xiao, Shun-min He, Guoqing Zhang, Yixue Li, Guoping Zhao, Runsheng Chen, Yingke Ma, Meili Chen, Cuiping Li, Shuai Jiang, Dong Zou, Zheng Gong, Xue-tong Zhao, Yanqing Wang, Junwei Zhu, Shuhui Song, Yunchao Ling, Yiwei Wang, Jiaxin Yang, Xinhao Zhuang, Guangya Duan, Gangao Wu, Xiaoning Chen, Dongmei Tian, Zhaohua Li, Yan-ling Sun, Zhenglin Du, Lili Hao, Yuan Gao, Bixia Tang, Yadong Zhang, Hao Zhang, Zaichao Zhang, Qiheng Qian, Zhewen Zhang, Hailong Kang, Tianhao Huang, Zhiqiang Xia, Xincheng Zhou, Jin-quan Chao, Zhonghuang Wang, Jun-wei Zhu, Sisi Zhang, Weimin Tian, Wenquan Wang, Song Wu, Yue Huang, Mochen Zhang, Guoliang Wang, Xin-chang Zheng, Wenting Zong, Wei Zhao, Peiqi Xing, Rujiao Li, Zhaoqi Liu, Mingming Lu, Fengchun Yang, Jialin Mai, Qianwen Gao, Xiaowei Xu, Hongyu Kang, Li Hou, Yunfei Shang, Qiheng Qain, Jie Liu, Meiye Jiang, Congfan Bu, Jinyue Wang, Jingyao Zeng, Jiao Li, Siyu Pan, Hongen Kang, Xinxuan Liu, Shiqi Lin, Na Yuan, Peilin Jia, Xinchang Zheng, Yanling Sun, Zhuang Xiong, Fei Yang, Xu Chen, Tingting Chen, Caixia Yu, Lili Dong, Shuang Zhai, Yubin Sun, Qiancheng Chen, Xiaoyu Yang, Xin Zhang, Zhengqi Sang, Yonggang Wang, Yilin Zhao, Huanxin Chen, Li Lan, Yan-qing Wang, Anke Wang, Yaokai Jia, Xuetong Zhao, Yitong Pan, Xiaonan Liu, Rongqin Zhang, Yi Wang, Lina Ma, Xufei Teng, Lun Li, Na Li, Ying Cui, Tong Jin, Enhui Jin, Tao Zhang, Tianyi Xu, Ming Chen, Guangyi Niu, Rong Pan, Tongtong Zhu, Yuan Chu, Jian Sang, Yuanpu Zhang, Zhennan Wang, Yuan-sheng Zhang, Qiliang Yao, Xinran Zhang, Xutong Guo, Zhao Li, Lin Liu, Changrui Feng, Yuxin Qin, Wei Jing, Sicheng Luo, Tong-tong Zhu, Yuansheng Zhang, Zis-han Wu, Qianpeng Li, Pei Liu, Yongqing Sun, Zhuojing Fan, Wen-ming Zhao, Wen-Kang Shen, An-Yuan Guo, Zhixiang Zuo, Jian Ren, Xinxin Zhang, Yun Xiao, Xia Li, Dan Liu, Chi Zhang, Yu Xue, Zheng Zhao, Tao Jiang, Wanying Wu, Fangqing Zhao, Xianwen Meng, Yujie Gou, Miaomiao Chen, Di Peng, Hao Luo, Feng Gao, Wanshan Ning, Wan Liu, Ruifang Cao, Guo-qing Zhang, Yuxiang Wei, Chun-Jie Liu, Gui-Yan Xie, Hao Yuan, Tianhan Su, Yong E. Zhang, Chenfen Zhou, Pengyu Wang, Yincong Zhou, Guoji Guo, Qiong Zhang, Shanshan Fu, Xiaodan Tan, Dachao Tang, Weizhi Zhang, Mei Luo, Yubin Xie, Ya-Ru Miao, Xinhe Huang, Zihao Feng, Xingyu Liao, Xin Gao, Jianxin Wang, Guiyan Xie, Chunhui Yuan, Dechang Yang, Feng Tian, Ge Gao, Wenyi Wu, Cheng Han, Qinghua Cui, Chunfu Xiao, Chuan-Yun Li, XiaoTong Luo, Qing Tang
Summary: The National Genomics Data Center (NGDC) of the China National Center for Bioinformation (CNCB) provides database resources to support global academic and industrial communities. The NGDC constantly expands and updates core database resources by archiving big data, conducting integrative analysis, and providing value-added curation. New database resources have been developed for infectious diseases and microbiology, cancer-trait association, and tropical plants. Additionally, resources for the monkeypox virus and SARS-CoV-2 have been newly constructed and regularly updated. All resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Kunxiang Liu, Bo Liu, Yuhong Zhang, Qinian Wu, Ming Zhong, Lindong Shang, Yu Wang, Peng Liang, Weiguo Wang, Qi Zhao, Bei Li
Summary: Cell misuse and cross-contamination can lead to inaccurate cell research results and wasted resources, making cell line identification important. Raman spectroscopy has emerged as a rapid and noninvasive method for identifying cell lines, with the potential to accurately identify gastric cancer cells. The study also highlights the usefulness of machine learning in classifying Raman spectral background data.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Oncology
Yan-Xing Chen, Zi-Xian Wang, Ying Jin, Qi Zhao, Ze-Xia Liu, Zhi-Xiang Zuo, Huai-Qiang Ju, Chengxu Cui, Jun Yao, Yanqiao Zhang, Mengxia Li, Jifeng Feng, Lin Tian, Xiao-Jun Xia, Hui Feng, Sheng Yao, Feng-Hua Wang, Yu-Hong Li, Feng Wang, Rui-Hua Xu
Summary: Although chemotherapy plus PD-1 blockade has become the standard first-line therapy for advanced esophageal squamous cell carcinoma (ESCC), reliable biomarkers for this regimen are lacking. Through whole-exome sequencing, the study identifies immunogenic features and oncogenic alterations associated with chemo+anti-PD-1 efficacy, and establishes an esophageal cancer genome-based immuno-oncology classification. The classification scheme guides individualized treatment strategies and informs biomarker research for chemo+anti-PD-1 treatment in patients with advanced ESCC.
Meeting Abstract
Oncology
Penghui Zhou, Jingjing He, Xinxin Xiong, Han Yang, Dandan Li, Xuefei Liu, Haiping Liu, Peirong Ding, Xiaoshi Zhang, Zhenjiang Liu, Wende Li, Zhixiang Zuo