检索结果-内蒙古大学图书馆

Proceedings of the 2023 10th International Conference on Biomedical and bioinformatics Engineering

作者： Hayeon Kim Myeongji Cho Hyeon S. Son Laboratory of Computational Biology & Bioinformatics Graduate School of Public Health Seoul National University Republic of Korea and Institute of Health and Environment Seoul National University Republic of Korea Laboratory of Computational Biology & Bioinformatics Graduate School of Public Health Seoul National University Republic of Korea Laboratory of Computational Biology & Bioinformatics Graduate School of Public Health Seoul National University Republic of Korea Institute of Health and Environment Seoul National University Republic of Korea and Interdisciplinary Graduate Program in Bioinformatics College of Natural Science Seoul National University Republic of Korea

ISBN: (纸本)9798400708343

MERS-CoV, which belongs to the beta-coronaviruses together with SARS-CoV-2, although it has received relatively less attention by the COVID-19 pandemic, there is a sufficient possibility of new MERS-CoV lineages and variants. Previous studies have discussed the possibility of frequent recombination of MERS-CoV. We thus present a highly accurate method for the phylogenetic analysis and classification of MERS-CoV including recombinant sequences. We collected the sequences of S protein from MERS-CoV and divided them into five phylogenetic groups, of which recombinant sequences were divided into seven types. Physicochemical properties of amino acids were then calculated from the S protein sequences, and the results were used for the random forest model, Naïve Bayes classification, and k-nearest neighbor method. We also constructed several feature subsets based on the ranked amino acid properties and applied them to the random forest model. In each dataset, the amino acid physicochemical properties were ranked differently. Using this information, classification of MERS-CoV based on machine learning algorithms showed that the random forest model had the best accuracy and area under the curve compared with the k-nearest neighbor and Naïve Bayes classification methods. Several feature subsets were constructed using the correlation feature selection algorithm and applied to the random forest model. Overall, the performance of the classifier was improved compared to that when using all features. Coronaviruses including MERS-CoV continue to evolve into new forms through recombination or mutation. We thus present a method to increase the accuracy of their classification using additional information of the viral protein sequence, and confirm that a subunit consisting of optimal prominent features can improve the performance of the classifier by removing the unnecessary characteristic information.

关键词： MERS-CoV classification machine learning

来源：评论

学校读者我要写书评

暂无评论

Crystallization of asymmetric patchy models for globular proteins in solution

引用

Physical Review E 2013年第1期88卷 012721-012721页

作者： Diana Fusco Patrick Charbonneau Program in Computational Biology and Bioinformatics Duke University Durham North Carolina 27708 USA Department of Chemistry Duke University Durham North Carolina 27708 USA Department of Physics Duke University Durham North Carolina 27708 USA

Asymmetric patchy particle models have recently been shown to describe the crystallization of small globular proteins with near-quantitative accuracy. Here, we investigate how asymmetry in patch geometry and bond energy generally impacts the phase diagram and nucleation dynamics of this family of soft matter models. We find the role of the geometry asymmetry to be weak, but the energy asymmetry to markedly interfere with the crystallization thermodynamics and kinetics. These results provide a rationale for the success and occasional failure of the proposal of George and Wilson for protein crystallization conditions as well as physical guidance for developing more effective protein crystallization strategies.

关键词： Crystallization asymmetric globular Crystallization soft matter Solutions globular protein globular shape Bond energy ASYMMETRIC Phase diagrams

来源：评论

学校读者我要写书评

暂无评论

Ribosomes guide pachytene piRNA formation on long intergenic piRNA precursors (vol 22, pg 200, 2020)

引用

NATURE CELL biology 2020年第3期22卷 353-353页

作者： Sun, Yu H. Zhu, Jiang Xie, Li Huitong Li, Ziwei Meduri, Rajyalakshmi Zhu, Xiaopeng Song, Chi Chen, Chen Ricci, Emiliano P. Weng, Zhiping Li, Xin Zhiguo Center for RNA Biology: From Genome to Therapeutics Department of Biochemistry and Biophysics University of Rochester Medical Center Rochester NY USA Computational Biology Department Carnegie Mellon University Pittsburgh PA USA College of Public Health Division of Biostatistics The Ohio State University Columbus OH USA Department of Animal Science Michigan State University East Lansing MI USA Université de Lyon ENSL UCBL INSERM CNRS LBMC Lyon France Program in Bioinformatics and Integrative Biology University of Massachusetts Medical School Worcester MA USA Department of Urology University of Rochester Medical Center Rochester NY USA

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： RNA Spermatogenesis

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous photocatalytic degradation of diuron on zinc oxide: Influence of surface-dependent adsorption on kinetics,degradation pathway,and toxicity of intermediates

引用

Journal of Environmental Sciences 2019年第10期31卷 97-111页

作者： Sutaporn Meephon Thanyada Rungrotmongkol Somchintana Puttamat Supareak Praserthdam Varong Pavarajarn Center of Excellence in Particle Technology Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand Biocatalyst and Environmental Biotechnology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn UniversityBangkok 10330 Thailand Bioinformatics and Computational Biology Program Graduated School Chulalongkorn University Bangkok 10330 Thailand Department of Chemistry Faculty of Science Thammasat University Pathumthani 12120 Thailand Center of Excellence on Catalysis and Catalytic Reaction Engineering Department of Chemical Engineering Faculty of EngineeringChulalongkorn University Bangkok 10330 Thailand Research Program in Hazardous Substance Management in Agricultural Industry Center of Excellence on Hazardous Substance Management(HSM) Bangkok 10330 Thailand

Heterogeneous photocatalytic reaction has been generally applied for degradation of toxic *** of a compound using the same kind of catalyst that was synthesized differently are commonly found in ***,the reported degradation intermediates are normally *** issue is especially important for the degradation of toxic compounds because intermediates may be more toxic than their parent compounds and understanding the reason is necessary if appropriate catalysts are to be *** work systematically compares the photocatalytic degradation of diuron,a toxic recalcitrant herbicide,on two forms of zinc oxide(ZnO),i.e.,conventional particles with zinc-and oxygen-terminated polar surfaces as the dominating planes,and nanorods with mixed-terminated nonpolar *** and theoretical results indicate that both the rate of reaction and the degradation pathway depend on the adsorption configuration of diuron onto the *** molecules adsorb in different alignments on the two surfaces,contributing to the formation of different degradation *** the aliphatic and aromatic sides of diuron adsorb on the polar surfaces simultaneously,leading to an attack by hydroxyl radicals from both *** the other hand,on the mixed-terminated surface,only the aliphatic part adsorbs and is *** exposed surface is therefore the key factor controlling the degradation *** diuron degradation on ZnO,a catalyst confined tomixed-terminated surfaces,i.e.,ZnO nanorods,is more desirable,as it avoids the formation of intermediates with potent phytotoxicity and cytogenotoxicity.

关键词： Diuron Photocatalysis Adsorption Degradation pathway Mechanism Toxicity

来源：评论

学校读者我要写书评

暂无评论

Data-driven modeling and prediction of microglial cell dynamics in the ischemic penumbra

arXiv

引用

arXiv 2024年

作者： Amato, Sara Arnold, Andrea Bioinformatics & Computational Biology Program Worcester Polytechnic Institute WorcesterMA United States Department of Mathematical Sciences Worcester Polytechnic Institute WorcesterMA United States

Neuroinflammation immediately follows the onset of ischemic stroke. During this process, microglial cells are activated in and recruited to the tissue surrounding the irreversibly injured infarct core, referred to as the penumbra. Microglial cells can be activated into two distinct phenotypes;however, the dynamics between the detrimental M1 phenotype and beneficial M2 phenotype are not fully understood. Using phenotype-specific cell count data obtained from experimental studies on middle cerebral artery occlusion-induced stroke in mice, we employ sparsity-promoting system identification techniques combined with Bayesian statistical methods for uncertainty quantification to generate continuous and discrete-time predictive models of the M1 and M2 microglial cell dynamics. The resulting data-driven models include constant and linear terms but do not include nonlinear interactions between the cells. Results emphasize an initial M2 dominance followed by a takeover of M1 cells, capture potential long-term dynamics of microglial cells, and suggest a persistent inflammatory response. Copyright © 2024, The Authors. All rights reserved.

关键词： Mammals

来源：评论

学校读者我要写书评

暂无评论

Identifying interaction sites in "Recalcitrant" proteins: Predicted protein and RNA binding sites in REV proteins of HIV-1 and EIAV agree with experimental data

Identifying interaction sites in "Recalcitrant" proteins: Pr...

引用

11th Pacific Symposium on Biocomputing 2006, PSB 2006

作者： Terribllini, Michael Lee, Jae-Hyung Yan, Changhui Jernigan, Robert L. Carpenter, Susan Honavar, Vasant Dobbs, Drena Bioinformatics and Computational Biology Graduate Program LH. Baker Center for Bioinformatics and Biological Statistics Iowa State University Ames IA 50010 United States Department of Computer Science Iowa State University Ames IA 50010 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50010 United States Department of Genetics Development and Cell Biology Iowa State University Ames IA 50010 United States Artificial Intelligence Research Laboratory Center for Computational Intelligence Learning and Discovery Iowa State University Ames IA 50010 United States Department of Veterinary Microbiology and Pathology Washington State University Pullman WA. 99164 United States

ISBN: (纸本)9812564632

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation or gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the proiein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites in the sequence of a clinically important protein for which the structure is not known: the regulatory protein Rev, essential for the replication of HIV-I and other lentiviruses. We compare our predictions with published biochemical, genetic and partial structural information for HIV-1 and EIAV Rev and with our own published experimental mapping of RNA binding sites in EIAV Rev. The predicted and experimentally determined binding sites are in very good agreement. The ability to predict reliably the residues of a protein that directly contribute to specific binding events - without the requirement for structural information regarding either the protein or complexes in which it participates - can potentially generate new disease intervention strategies.

关键词： Binding sites

来源：评论

学校读者我要写书评

暂无评论

Scalable algorithms for learning high-dimensional linear mixed models

arXiv

引用

arXiv 2018年

作者： Tan, Zilong Roche, Kimberly Zhou, Xiang Mukherjee, Sayan Department of Computer Science Duke University Program in Computational Biology & Bioinformatics Duke University Department of Biostatistics Center for Statistical Genetics University of Michigan Departments of Statistical Science Mathematics Computer Science Biostatistics & Bioinformatics Duke University

Linear mixed models (LMMs) are used extensively to model dependecies of observations in linear regression and are used extensively in many application areas. Parameter estimation for LMMs can be computationally prohibitive on big data. State-of-the-art learning algorithms require computational complexity which depends at least linearly on the dimension p of the covariates, and often use heuristics that do not offer theoretical guarantees. We present scalable algorithms for learning high-dimensional LMMs with sublinear computational complexity dependence on p. Key to our approach are novel dual estimators which use only kernel functions of the data, and fast computational techniques based on the subsampled randomized Hadamard transform. We provide theoretical guarantees for our learning algorithms, demonstrating the robustness of parameter estimation. Finally, we complement the theory with experiments on large synthetic and real data. Copyright © 2018, The Authors. All rights reserved.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

A data-informed mathematical model of microglial cell dynamics during ischemic stroke in the middle cerebral artery

arXiv

引用

arXiv 2024年

Neuroinflammation immediately follows the onset of ischemic stroke in the middle cerebral artery. During this process, microglial cells are activated in and recruited to the penumbra. Microglial cells can be activated into two different phenotypes: M1, which can worsen brain injury;or M2, which can aid in long-term recovery. In this study, we contribute a summary of experimental data on microglial cell counts in the penumbra following ischemic stroke induced by middle cerebral artery occlusion (MCAO) in mice and compile available data sets into a single set suitable for time series analysis. Further, we formulate a mathematical model of microglial cells in the penumbra during ischemic stroke due to MCAO. Through use of global sensitivity analysis and Markov Chain Monte Carlo (MCMC)-based parameter estimation, we analyze the effects of the model parameters on the number of M1 and M2 cells in the penumbra and fit identifiable parameters to the compiled experimental data set. We utilize results from MCMC parameter estimation to ascertain uncertainty bounds and forward predictions for the number of M1 and M2 microglial cells over time. Results demonstrate the significance of parameters related to M1 and M2 activation on the number of M1 and M2 microglial cells. Simulations further suggest that potential outliers in the observed data may be omitted and forecast predictions suggest a lingering inflammatory response. Copyright © 2024, The Authors. All rights reserved.

关键词： Parameter estimation

来源：评论

学校读者我要写书评

暂无评论

Particle-based simulations reveal two positive feedback loops allow relocation and stabilization of the polarity site during yeast mating

引用

PLoS computational biology 2023年第10 October期19卷 e1011523-e1011523页

作者： Guan, Kaiyun Curtis, Erin R. Lew, Daniel J. Elston, Timothy C. Curriculum in Bioinformatics and Computational Biology University of North Carolina at Chapel Hill Chapel HillNC United States Department of Biology Massachusetts Institute of Technology CambridgeMA United States Department of Pharmacology and Computational Medicine Program University of North Carolina at Chapel Hill Chapel HillNC United States

Many cells adjust the direction of polarized growth or migration in response to external directional cues. The yeast Saccharomyces cerevisiae orient their cell fronts (also called polarity sites) up pheromone gradients in the course of mating. However, the initial polarity site is often not oriented towards the eventual mating partner, and cells relocate the polarity site in an indecisive manner before developing a stable orientation. During this reorientation phase, the polarity site displays erratic assembly-disassembly behavior and moves around the cell cortex. The mechanisms underlying this dynamic behavior remain poorly understood. Particle-based simulations of the core polarity circuit revealed that molecular-level fluctuations are unlikely to overcome the strong positive feedback required for polarization and generate relocating polarity sites. Surprisingly, inclusion of a second pathway that promotes polarity site orientation generated relocating polarity sites with properties similar to those observed experimentally. This pathway forms a second positive feedback loop involving the recruitment of receptors to the cell membrane and couples polarity establishment to gradient sensing. This second positive feedback loop also allows cells to stabilize their polarity site once the site is aligned with the pheromone gradient. © 2023 Guan et al.

关键词： Cells

来源：评论

学校读者我要写书评

暂无评论

Research in computational Molecular biology 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Minghua Deng Rui Jiang Fengzhu Sun Xuegong Zhang

ISBN: (数字)9783642371950

ISBN: (纸本)9783642371943

This book constitutes the refereed proceedings of the 17th Annual International Conference on Research in computational Molecular biology, RECOMB 2013, held in Beijing, China, in April 2013. The 32 revised full papers were carefully reviewed and selected from 167 submissions. The papers cover a wide range of topics including molecular sequence analysis; genes and regulatory elements; molecular evolution; gene expression; biological networks; sequencing and genotyping technologies; genomics; epigenomics; metagenomics; population, statistical genetics; systems biology; computational proteomics; computational structural biology; imaging; large-scale data management.

关键词： computational biology/bioinformatics Mathematical and computational biology Data Mining and Knowledge Discovery Algorithm Analysis and Problem Complexity

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：