Article
Biochemistry & Molecular Biology
Panyu Ren, Xiaodi Yang, Tianpeng Wang, Yunpeng Hou, Ziding Zhang
Summary: This study predicted the protein-protein interaction (PPI) network of Cryptosporidium parvum (C. parvum) using three bioinformatics methods and explored the biological significance of the network. The constructed PPI network can serve as a valuable data resource for functional genomics studies and target discovery in drug/vaccine development for C. parvum.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Biochemistry & Molecular Biology
Athena Lin, Paul D. Piehowski, Chia-Feng Tsai, Tatyana Makushok, Lian Yi, Ulises Diaz, Connie Yan, Diana Summers, Pranidhi Sood, Richard D. Smith, Tao Liu, Wallace F. Marshall
Summary: Cellular components are not randomly arranged with respect to the shape and polarity of the whole cell. The patterning within cells can extend to the level of individual proteins and mRNA. Proteomics combined with cellular fractionation has shown that most proteins localize to organelles but not how many have a polarized localization with respect to the large-scale polarity axes of the intact cell. The giant ciliate Stentor coeruleus provides a visible global pattern for analyzing protein distribution within a cell.
Article
Biology
Zilong Hou, Yuning Yang, Zhiqiang Ma, Ka-chun Wong, Xiangtao Li
Summary: Protein-protein interactions (PPIs) play a crucial role in cellular pathways and processes, but accurate identification of PPI binding sites is challenging. The proposed EDLM-based method, EDLMPPI, addresses these challenges by utilizing an ensemble deep learning model. Evaluation results demonstrate that EDLMPPI outperforms state-of-the-art techniques in terms of average precision on widely-used benchmark datasets. Additionally, the method provides new insights into protein binding site identification and characterization mechanisms.
COMMUNICATIONS BIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Carlos Henrique Vieira-Vieira, Vita Dauksaite, Anje Sporbert, Michael Gotthardt, Matthias Selbach
Summary: Researchers have developed a quantitative RNA-interactome capture method to assess the function of phosphorylation sites in RNA-binding proteins.
Article
Biochemical Research Methods
Juan R. Lorenzo, Cesar O. Leonetti, Leonardo G. Alonso, Ignacio E. Sanchez
Summary: Researchers have developed a new algorithm for predicting spontaneous protein deamidation, which is faster and similarly accurate compared to current algorithms. The algorithm takes into account sequence propensities and structural protection to predict the half-life of intact form for each protein. The analysis shows that different taxa exhibit different deamidation dynamics.
Article
Metallurgy & Metallurgical Engineering
Qing-qing Shen, Qiu-hua Rao, Zhuo Li, Wei Yi, Dong-liang Sun
Summary: The maximum Mode I and Mode II stress intensity factors of inclined parallel multi-crack were calculated using complex function and integration method to analyze their interacting mechanism and determine the strengthening and weakening zone of SIFs. A multi-crack initiation criterion was established based on the ratio of maximum tension-shear SIF to predict crack initiation angle, load, and mechanism.
TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA
(2021)
Article
Biochemistry & Molecular Biology
Yangchun Frank Chen, Yu Xia
Summary: This study focused on the potential of bacterial protein structural components to engage in or target eukaryote-specific domain-domain interactions (DDIs). It found that effectors are more likely to contain host-like domains and target host DDIs, as well as harbor a higher variety and density of short linear motifs targeting host domains. These insights provide a quantitative understanding of effector-induced perturbation of host-endogenous PPIs and may aid in the design of selective inhibitors of host-pathogen interactions.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Linjuan Wang, Xingqi Huang, Kui Li, Shuyuan Song, Yunhe Jing, Shan Lu
Summary: Chloroplasts are semi-autonomous organelles that rely on precise coordination between their own genomes and the nucleus for functioning correctly. The protein GENOMES UNCOUPLED 1 (GUN1) plays a key role in integrating physiological signals and regulating developmental processes. Through yeast two-hybrid screening, 15 potential interacting proteins with GUN1 were identified, with two, DJC31 and HCF145, confirmed to interact in plant cells. Further investigation of these interactions revealed insights into the molecular mechanisms underlying GUN1-mediated regulations.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemical Research Methods
Mustafa Coskun, Mehmet Koyuturk
Summary: Using node similarity-based convolution matrices in GCNs can significantly improve the link prediction performance of GCN-based embeddings. Experimental results in biomedical networks show that this approach can enhance the performance of link prediction.
Article
Multidisciplinary Sciences
Weishu Zhao, Bozitao Zhong, Lirong Zheng, Pan Tan, Yinzhao Wang, Hao Leng, Nicolas de Souza, Zhuo Liu, Liang Hong, Xiang Xiao
Summary: This study investigates the ancestral metabolism of ancient bacteria and archaea by comparing their protein structures. The research reveals similar physiological and metabolic characteristics between the two groups and identifies conserved metabolic modules. These findings provide a new perspective on reconstructing ancestral metabolism and understanding its origin.
NATURE COMMUNICATIONS
(2022)
Article
Computer Science, Theory & Methods
Benoit Bonnet, Teddy Furon, Patrick Bas
Summary: This paper proposes a method dedicated to quantizing adversarial perturbations while minimizing quantization error and maintaining image adversarial after quantization. The method operates in both spatial and JPEG domains with low complexity.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2022)
Article
Biochemistry & Molecular Biology
Wei Qin, Joleen S. Cheah, Charles Xu, James Messing, Brian D. Freibaum, Steven Boeynaems, J. Paul Taylor, Namrata D. Udeshi, Steven A. Carr, Alice Y. Ting
Summary: The ability to map trafficking for thousands of endogenous proteins at once in living cells reveals biology currently invisible to microscopy and mass spectrometry. The method TransitID uses proximity labeling enzymes TurboID and APEX to map endogenous proteome trafficking with nanometer spatial resolution. TransitID allows for distinguishing protein populations based on their origin compartment or cell type.
Article
Transportation Science & Technology
Yong Chen, Xiqun (Michael) Chen
Summary: A novel reinforced dynamic graph convolutional network model is proposed in this paper for data imputation and network-wide traffic flow prediction. The model effectively handles missing traffic data, extracts features, and predicts traffic flow, which is significant for traffic management and congestion mitigation.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Mechanics
Ali Kashefi, Tapan Mukerji
Summary: The study proposes a novel deep learning framework for predicting permeability of porous media from digital images, overcoming memory restrictions of GPUs through the use of PointNet architecture. This approach allows for larger batch sizes and faster, accurate predictions of permeability of digital rocks. Comparisons with convolutional neural networks show improved performance and generalizability of the proposed deep learning strategy.
Article
Genetics & Heredity
Majid Nikpay, Sepehr Ravati, Ruth McPherson
Summary: This study identified DNA methylation sites that impact the proteome and made the results available as freeware for biological insight. The research demonstrated that epigenomic modifications at DNA sites can influence protein levels, with methylation of certain sites contributing to the onset of diseases.
Article
Multidisciplinary Sciences
Yang Li, Ping Xie, Liang Lu, Jian Wang, Lihong Diao, Zhongyang Liu, Feifei Guo, Yangzhige He, Yuan Liu, Qin Huang, Han Liang, Dong Li, Fuchu He
NATURE COMMUNICATIONS
(2017)
Article
Biochemical Research Methods
Dong Li, Wanlin Liu, Zhongyang Liu, Jian Wang, Qijun Liu, Yunping Zhu, Fuchu He
MOLECULAR & CELLULAR PROTEOMICS
(2008)
Article
Biochemistry & Molecular Biology
Jian Wang, Keke Huo, Lixin Ma, Liujun Tang, Dong Li, Xiaobi Huang, Yanzhi Yuan, Chunhua Li, Wei Wang, Wei Guan, Hui Chen, Chaozhi Jin, Junchen Wei, Wanqiao Zhang, Yongsheng Yang, Qiongming Liu, Ying Zhou, Cuili Zhang, Zhihao Wu, Wangxiang Xu, Ying Zhang, Tao Liu, Donghui Yu, Yaping Zhang, Liang Chen, Dewu Zhu, Xing Zhong, Lixin Kang, Xiang Gan, Xiaolan Yu, Qi Ma, Jing Yan, Li Zhou, Zhongyang Liu, Yunping Zhu, Tao Zhou, Fuchu He, Xiaoming Yang
MOLECULAR SYSTEMS BIOLOGY
(2011)
Article
Multidisciplinary Sciences
Zhongyang Liu, Feifei Guo, Yong Wang, Chun Li, Xinlei Zhang, Honglei Li, Lihong Diao, Jiangyong Gu, Wei Wang, Dong Li, Fuchu He
SCIENTIFIC REPORTS
(2016)
Article
Biochemistry & Molecular Biology
Zhongyang Liu, Jiale Liu, Xinyue Liu, Xun Wang, Qiaosheng Xie, Xinlei Zhang, Xiangya Kong, Mengqi He, Yuting Yang, Xinru Deng, Lele Yang, Yaning Qi, Jiajun Li, Yuan Liu, Liying Yuan, Lihong Diao, Fuchu He, Dong Li
Summary: Only some cancer patients can benefit from chemotherapy and targeted therapy currently, with drug resistance being a major challenge. CTR-DB database collects and processes 83 patient-derived clinical transcriptomic datasets, offering opportunities for research and exploration in cancer drug response.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Cell Biology
Yuan Liu, Ruirui He, Yingjie Qu, Yuan Zhu, Dianke Li, Xinping Ling, Simin Xia, Zhenqiu Li, Dong Li
Summary: Understanding the relationship between genes and abnormal phenotypes is crucial for disease prevention, diagnosis, and treatment. However, the current annotations of human phenotypes are incomplete. To address this, a computational method called GraphPheno was developed to predict protein-phenotype associations by considering protein sequences and the protein-protein interaction network. The performance of GraphPheno was validated through cross validation and independent dataset tests, and it outperformed existing methods in automatic HPO annotation. The algorithm was also able to predict phenotype-associated genes with similar biological properties to known ones.