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HPC-Atlas:Computationally Constructing A Comprehensive Atlas of Human Protein Complexes

Genomics, Proteomics & bioinformatics 2023年第5期21卷 976-990页

作者： Yuliang Pan Ruiyi Li Wengen Li Liuzhenghao Lv Jihong Guan Shuigeng Zhou department of computer science and Technology College of Electronic and Information EngineeringTongji UniversityShanghai 201804China Translational Medical center for Stem Cell Therapy Shanghai East HospitalSchool of MedicineTongji UniversityShanghai 200120China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of *** a complete understanding of human cellular functions,it is crucial to have a comprehensive atlas of human protein ***,we still lack such a comprehensive atlas of experimentally validated protein complexes,which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes,as well as the underlying biological *** fill this gap,we built Human Protein Complexes Atlas(HPC-Atlas),as far as we know,the most accurate and comprehensive atlas of human protein complexes available to *** integrated two latest protein interaction networks,and developed a novel computational method to identify nearly 9000 protein complexes,including many previously uncharacterized *** with the existing methods,our method achieved outstanding performance on both testing and independent ***,with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-affected human protein complexes,and 456 multifunctional proteins that contain many potential moonlighting *** results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources,but also a valuable resource for exploring new biological *** HPCAtlas webserver is freely available at http://***/HPC-Atlas.

关键词： Human protein complex Protein interaction network SARS-CoV-2-affected complex Multifunctional protein Complex identification method

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Multi-interface collaboration of graphene cross-linked NiS-NiS_(2)-Ni_(3)S_(4) polymorph foam towards robust hydrogen evolution in alkaline electrolyte

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Nano Research 2021年第12期14卷 4857-4864页

作者： Haiqing Wang Wenjing Zhang Xiaowei Zhang Shuxian Hu Zhicheng Zhang Weijia Zhou Hong Liu Collaborative Innovation center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinan250022China Beijing Computational science Research center Beijing100193China Tianjin Key Laboratory of Molecular Optoelectronic sciences Department of ChemistrySchool of ScienceTianjin UniversityTianjin300072China State Key Laboratory of Crystal Materials Shandong UniversityJinan250100China

Electrocatalytic hydrogen production in alkaline media is extensively adopted in industry. Unfortunately, further performance improvement is severely impeded by the retarded kinetics, which requires the fine regulation of water dissociation, hydrogen recombination, and hydroxyl desorption. Herein, we develop a multi-interface engineering strategy to make an elaborate balance for the alkaline hydrogen evolution reaction (HER) kinetics. The graphene cross-linked three-phase nickel sulfide (NiS-NiS_(2)-Ni_(3)S_(4)) polymorph foam (G-NNNF) was constructed through hydrothermal sulfidation of graphene wrapped nickel foam as a three-dimensional (3D) scaffold template. The G-NNNF exhibits superior catalytic activity toward HER in alkaline electrolyte, which only requires an overpotential of 68 mV to drive 10 mA·cm^(−2) and is better than most of the recently reported metal sulfides catalysts. Density functional theory (DFT) calculations verify the interfaces between nickel sulfides (NiS/NiS_(2)-Ni_(3)S_(4)) and cross-linked graphene can endow the electrocatalyst with preferable hydrogen adsorption as well as metallic nature. In addition, the electron transfer from Ni_(3)S_(4)/NiS_(2) to NiS results in the electron accumulation on NiS and the hole accumulation on Ni_(3)S_(4)/NiS_(2), respectively. The electron accumulation on NiS favors the optimization of the H* adsorption, whereas the hole accumulation on Ni_(3)S_(4) is beneficial for the adsorption of H_(2)O. The work about multi-interface collaboration pushes forward the frontier of excellent polymorph catalysts design.

关键词： hydrogen evolution reaction nickel sulfide interface engineering polymorph heterointerface

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EZH2-, CHD4-, and IDH-linked epigenetic perturbation and its association with survival in glioma patients

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Journal of Molecular Cell Biology 2017年第6期9卷 477-488页

作者： Le Zhang Ying Liu Mengning Wang Zhenhai Wu Na Li Jinsong Zhang Chuanwei Yang College of computer science Sichuan University Chengdu China College of computer and Information science Southwest University Chongqing China The Vivian Smith department of Neurosurgery Center for Stem Cell and Regenerative Medicine The University of Texas Health Science Center at Houston Houston TX USA Harvard Stem Cell Institute Harvard University Cambridge MA USA department of neurosurgery ShouGuang People's Hospital Shandong China Pharmacological & Physiological science School of Medicine Saint Louis University St. Louis MO USA Breast Medical Oncology The University of Texas MD Anderson Cancer Center Houston TX USA Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA

GUoma is a complex disease with limited treatment options. Recent advances have identified isocitrate dehydrogenase （IDH） mutations in up to 80% lower grade gUomas （LGG） and in 76% secondary gUoblastomas （GBM）. IDH mutations are also seen in 10%-20% of acute myeloid leukemia （AML）. In AML, it was determined that mutations of IDH and other genes involving epigenetic regulations are early events, emerging in the pre-leukemic stem cells （pre-LSCs） stage, whereas mutations in genes propa- gating oncogenic signal are late events in leukemia. IDH mutations are also early events in gUoma, occurring before TP53 mutation, 1p/19q deletion, etc. Despite these advances in gUoma research, studies into other molecular alterations have lagged considerably. In this study, we analyzed currently available databases. We identified EZH2, KMT2C, and CHD# as important genes in glioma in addition to the known gene IDH1/2. We also showed that genomic alterations of PIK3CA, CDKN2A, CDK#, FIPIL1, or FUBP1 collaborate with IDH mutations to negatively affect patients＇ survival in LGG. In LGG patients with TP53 mutations or IDH1/2 mutations, additional genomic alterations of EZH2, KMC2C, and CHD4 individually or in combination were associated with a markedly decreased disease-free survival than patients without such alterations. Alterations of EZH2, KMT2C, and CHD4, at gen- etic level or protein level could perturb epigenetic program, leading to malignant transformation in glioma. By reviewing current literature on both AML and gUoma and performing bioinformatics analysis on available datasets, we developed a hypothetical model on the tumorigenesis from premaUgnant stem cells to gUoma.

关键词： glioma epigenetics bioinformatics prognosis gene mutation

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First Insights into the Viral Communities of the Deep-sea Anoxic Brines of the Red Sea

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Genomics, Proteomics & bioinformatics 2015年第5期13卷 304-309页

作者： Andr Antunes Intikhab Alam Marta Filipa Simoes Camille Daniels Ari J.S.Ferreira Rania Siam Hamza El-Dorry Vladimir B.Bajic Computational Bioscience Research center (CBRC) ComputerElectrical and Mathematical Sciences and Engineering Division (CEMSE)King Abdullah University of Science and Technology (KAUST) Red Sea Research center (RSRC) Biological and Environmental Sciences and Engineering Division (BESE)King Abdullah University of Science and Technology (KAUST) Biology department American University in Cairo

The deep-sea brines of the Red Sea include some of the most extreme and unique envi- ronments on Earth. They combine high salinities with increases in temperature, heavy metals, hydrostatic pressure, and anoxic conditions, creating unique settings for thriving populations of novel extremophiles. Despite a recent increase of studies focusing on these unusual biotopes, their viral communities remain unexplored. The current survey explores four metagenomic datasets obtained from different brine-seawater interface samples, focusing specifically on the diversity of their viral communities. Data analysis confirmed that the particle-attached viral communities present in the brine-seawater interfaces were diverse and generally dominated by Candovirales, yet appearing distinct from sample to sample. With a level of caution, we report the unexpected finding of Phycodnaviridae, which infects algae and plants, and trace amounts of insect-infecting Iridoviridae. Results from Kebrit Deep revealed stratification in the viral communities present in the interface： the upper-interface was enriched with viruses associated with typical marine bacteria, while the lower-interface was enriched with haloviruses and halophages. These results provide first insights into the unexplored viral communities present in deep-sea brines of the Red Sea, represent- ing one of the first steps for ongoing and future sampling efforts and studies.

关键词： Viral diversity Metagenomics Brine-seawater interface Caudovirales Red Sea

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A Dynamical Study of Modeling the Transmission of Typhoid Fever throughDelayed Strategies

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computer Modeling in Engineering & sciences 2024年第11期141卷 1419-1446页

作者： Muhammad Tashfeen Fazal Dayan Muhammad Aziz Ur Rehman Thabet Abdeljawad Aiman Mukheimer department of Mathematics School of ScienceUniversity of Management and TechnologyLahore54000Pakistan department of Mathematics and sciences Prince Sultan UniversityP.O.Box 66833Riyadh11586Saudi Arabia department of Medical Research China Medical UniversityTaichung40402TaiwanChina department of Mathematics and Applied Mathematics School of Science and TechnologySefakoMakgatho Health Sciences UniversityGa-Rankuwa0208South Africa center for Applied Mathematics and bioinformatics(CAMB) Gulf University for Science and TechnologyHawally32093Kuwait

This study analyzes the transmission of typhoid fever caused by Salmonella typhi using a mathematical model thathighlights the significance of delay in its *** delays can affect the nature of patterns and slow downthe emergence of patterns in infected population *** analyzed model is expanded with the equilibriumanalysis,reproduction number,and stability *** study aims to establish and explore the non-standardfinite difference(NSFD)scheme for the typhoid fever virus transmission model with a time *** addition,the forward Euler method and Runge-Kutta method of order 4(RK-4)are also applied in the present *** significant properties,such as convergence,positivity,boundedness,and consistency,are explored,and theproposed scheme preserves all the mentioned *** theoretical validation is conducted on how NSFDoutperforms other methods in emulating key aspects of the continuous model,such as positive solution,stability,and equilibrium about ***,the above analysis also shows some of the limitations of the conventional finitedifference methods,such as forward Euler and RK-4 in simulating such critical *** becomes moreapparent when using larger *** indicated that NSFD is beneficial in identifying the essential characteristicsof the continuous model with higher accuracy than the traditional approaches.

关键词： Typhoid virus delay epidemic model stability consistency global stability

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Deep Learning Deepens the Analysis of Alternative Splicing

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Genomics, Proteomics & bioinformatics 2019年第2期17卷 219-221页

作者： Xudong Zou Xin Gao Wei Chen department of Biology Southern University of Science and Technology Shenzhen 518055 China Computational Bioscience Research center (CBRC) Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia

The ever-increasing high-volume and high-dimensional geno-mics data on the one hand challenge traditional data analysis approaches,and on the other hand provide ample opportuni-ties for developing novel analytic strat... 详细信息

关键词： Deep Learning Deepens the Analysis Alternative Splicing

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LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

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computer Modeling in Engineering & sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui department of computer science and Information Engineering Asia UniversityTaichung413TaiwanChina Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India center for interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India computer Engineering Ronin InstituteMontclairNJ 07043USA Management department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Business Administration Asia UniversityTaichung413TaiwanChina department of Electrical and computer Engineering Lebanese American UniversityBeirut1102Lebanon department of computer sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of science and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

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Synthetic gene circuits moving into the clinic

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Quantitative Biology 2021年第1期9卷 100-103页

作者： Shuguang Peng Huiya Huang Ping Wei Zhen Xie MOE Key Laboratory of bioinformatics and bioinformatics Division Center for Synthetic and System BiologyDepartment of AutomationBeijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China Beijing Syngentech Co. LtdZhongguancun Life Science ParkChangping DistrictBeijing 102206China center for Gene Circuit and Cell Design Shenzhen Institute of Synthetic BiologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055ChinaCenter for Quantitative BiologyAcademy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China

On November 28th 2020,SyngenTech,a China-based biotechnology company,announced that the company’s leading oncolytic virotherapeutic product,SynOVl.l,was approved for clinical trial by the *** and Drug *** synthetic bacterial or cell therapy[1,2],this is the first introduction of a viral therapy engineered using synthetic gene circuits into the *** with the clinical development of variable living therapeutics,we anticipate that synthetic gene circuits will receive increasing attention as a revolutionary technology to improve disease-treatment efficacy.

关键词： clinic clinical Together

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An enrichment model using regular health examination data for early detection of colorectal cancer

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Chinese Journal of Cancer Research 2019年第4期31卷 686-698页

作者： Qiang Shi Zhaoya Gao Pengze Wu Fanxiu Heng Fuming Lei Yanzhao Wang Qingkun Gao Qingmin Zeng Pengfei Niu Cheng Li Jin Gu department of General Surgery Shougang HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Peking-Tsinghua center for Life sciences Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Department of Information TechnologyPeking University Cancer Hospital&InstituteBeijing 100142China center for Statistical science Center for BioinformaticsPeking UniversityBeijing 100871China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Department of Gastrointestinal SurgeryPeking University Cancer Hospital&InstituteBeijing 100142China

Objective: Challenges remain in current practices of colorectal cancer(CRC) screening, such as low compliance,low specificities and expensive cost. This study aimed to identify high-risk groups for CRC from the general population using regular health examination ***: The study population consist of more than 7,000 CRC cases and more than 140,000 controls. Using regular health examination data, a model detecting CRC cases was derived by the classification and regression trees(CART) algorithm. Receiver operating characteristic(ROC) curve was applied to evaluate the performance of models. The robustness and generalization of the CART model were validated by independent datasets. In addition, the effectiveness of CART-based screening was compared with stool-based ***: After data quality control, 4,647 CRC cases and 133,898 controls free of colorectal neoplasms were used for downstream analysis. The final CART model based on four biomarkers(age, albumin, hematocrit and percent lymphocytes) was constructed. In the test set, the area under ROC curve(AUC) of the CART model was 0.88 [95%confidence interval(95% CI), 0.87-0.90] for detecting CRC. At the cutoff yielding 99.0% specificity, this model’s sensitivity was 62.2%(95% CI, 58.1%-66.2%), thereby achieving a 63-fold enrichment of CRC cases. We validated the robustness of the method across subsets of test set with diverse CRC incidences, aging rates, genders ratio, distributions of tumor stages and locations, and data sources. Importantly, CART-based screening had the higher positive predictive value(1.6%) than fecal immunochemical test(0.3%).Conclusions: As an alternative approach for the early detection of CRC, this study provides a low-cost method using regular health examination data to identify high-risk individuals for CRC for further examinations. The approach can promote early detection of CRC especially in developing countries such as China, where annual health examination is popular but reg

关键词： Classification and regression trees colorectal cancer regular health examination data routine lab test biomarkers

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Advanced BERT and CNN-Based Computational Model for Phishing Detection in Enterprise Systems

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computer Modeling in Engineering & sciences 2024年第12期141卷 2165-2183页

作者： Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui department of computer science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India center for interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India computer Engineering Ronin InstituteMontclairNJ 07043USA department of Business Administration Asia UniversityTaichung413Taiwan department of Electrical and computer Engineering Lebanese American UniversityBeirut1102Lebanon College of Business Administration Management DepartmentPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia department of Research and Innovation Insights2TechinfoJaipur302001India department of computer sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia department of Electronic Engineering and computer science Hong Kong Metropolitan University(HKMU)Hong Kong518031China

Phishing attacks present a serious threat to enterprise systems,requiring advanced detection techniques to protect sensitive *** study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers(BERT)for feature extraction and CNN for classification,specifically designed for enterprise information ***’s linguistic capabilities are used to extract key features from email content,which are then processed by a convolutional neural network(CNN)model optimized for phishing *** an accuracy of 97.5%,our proposed model demonstrates strong proficiency in identifying phishing *** approach represents a significant advancement in applying deep learning to cybersecurity,setting a new benchmark for email security by effectively addressing the increasing complexity of phishing attacks.

关键词： Phishing BERT convolutional neural networks email security deep learning

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