检索结果-内蒙古大学图书馆

20th International Workshop on Algorithms in bioinformatics, WABI 2020

作者： Jahn, Katharina Beerenwinkel, Niko Zhang, Louxin Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland SIB Swiss Institute of Bioinformatics Basel Switzerland Department of Mathematics and Computational Biology Program National University of Singapore Singapore

ISBN: (纸本)9783959771610

Mutation trees are rooted trees of arbitrary node degree in which each node is labeled with a mutation set. These trees, also referred to as clonal trees, are used in computational oncology to represent the mutational history of tumours. Classical tree metrics such as the popular RobinsonFoulds distance are of limited use for the comparison of mutation trees. One reason is that mutation trees inferred with different methods or for different patients often contain different sets of mutation labels. Here, we generalize the RobinsonFoulds distance into a set of distance metrics called Bourque distances for comparing mutation trees. A connection between the RobinsonFoulds distance and the nearest neighbor interchange distance is also presented. © Katharina Jahn, Niko Beerenwinkel, and Louxin Zhang;licensed under Creative Commons License CC-BY

关键词： Bourque distance Clonal trees Mutation trees Phylogenetic trees Robinson–Foulds distance Tree distance Tree metric

来源：评论

学校读者我要写书评

暂无评论

In vitro and in vivo toxicity assessment of the senotherapeutic Peptide 14

引用

Toxicology Reports 2022年 9卷 1632-1638页

作者： Zonari, Alessandra Brace, Lear E. Alencar-Silva, Thuany Porto, William F. Foyt, Daniel Guiang, Mylieneth Cruz, Edgar Andres Ochoa Franco, Octavio L. Oliveira, Carolina R. Boroni, Mariana Carvalho, Juliana L. OneSkin Inc San Francisco 94107 CA United States Genomic Sciences and Biotechnology Program Catholic University of Brasilia DF Brasília 70790-160 Brazil DF Brasília 72236–011 Brazil Center of Proteomic Analyses and Biochemistry Genomic Sciences and Biotechnology Program Catholic University of Brasilia DF Brasilia 70790-160 Brazil S-Inova Biotech Biotechnology Program Catholic University Dom Bosco MS Campo Grande 79117-010 Brazil Molecular Pathology Program University of Brasilia DF Brasilia 70.910-900 Brazil Bioinformatics and Computational Biology Lab Brazilian National Cancer Institute (INCA) RJ Rio de Janeiro 20231-050 Brazil Interdisciplinary Biosciences Laboratory Faculty of Medicine University of Brasília DF Brasília 70.910–900 Brazil

Senotherapeutic molecules decrease cellular senescence burden, constituting promising approaches to combat the accumulation of senescent cells observed in chronological aging and age-related diseases. Numerous molecules have displayed senotherapeutic potential, but toxicity has been frequently observed. Recently, a new senotherapeutic compound, Peptide 14, was developed to modulate cellular senescence in the skin. In order to assess the potential toxic and genotoxic effects of the peptide, we observed the viability of human primary dermal fibroblasts and epidermal keratinocytes with Peptide 14 treatment, and show that it is mostly non-toxic in concentrations up to 100 μM. Cancer lines were also used to investigate its potential of modulating proliferation. Different concentrations of the peptide promoted a discrete reduction in the proliferation of cancerous cells of the MeWo and HeLa lineages. In full-thickness human skin equivalents, topically formulated Peptide 14 also failed to exert any significant irritation, nor cellular toxicity when added to the culture media. Genotoxic assays including the Ames, micronucleus, and karyotyping tests also indicate the safety of the peptide. Finally, the irritative potential of the peptide was assessed in human subjects in a repeated insult patch test executed using 1 mM peptide. No visible skin reactions were observed in any of the 54 participants. Taken together, the present data support that Peptide 14 is a senotherapeutic molecule with a positive safety profile as tested with cruelty-free models, justifying further studies involving the peptide. © 2022 The Authors

关键词： 3D skin equivalents Aging Cellular senescence In-vitro toxicology Peptide 14 RIPT

来源：评论

学校读者我要写书评

暂无评论

CIWARS: A Web Server for Antibiotic Resistance Surveillance Using Longitudinal Metagenomic Data

引用

Journal of Molecular biology 2025年

作者： Emon, Muhit Islam Cheung, Yat Fei Stoll, James Rumi, Monjura Afrin Brown, Connor Choi, Joung Min Moumi, Nazifa Ahmed Ahmed, Shafayat Song, Haoqiu Sein, Justin Yao, Shunyu Khan, Ahmad Gupta, Suraj Kulkarni, Rutwik Butt, Ali Vikesland, Peter Pruden, Amy Zhang, Liqing Department of Computer Science Virginia Tech Blacksburg 24060 VA United States Fralin Life Science Institute Virginia Tech Blacksburg 24060 VA United States Department of Civil and Environmental Engineering Virginia Tech Blacksburg 24060 VA United States The Interdisciplinary PhD Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg 24060 VA United States

The rise of antibiotic resistance (AR) poses a substantial threat to human and animal health, food security, and economic stability. Wastewater-based surveillance (WBS) has emerged as a powerful strategy for population-level AR monitoring, providing valuable data to guide public health and policy decisions. Metagenomic sequencing is especially promising, as it can yield comprehensive profiles of antibiotic resistance genes (ARGs) and other genes relevant to AR in a single run. However, online analytical platforms to facilitate analysis of longitudinal metagenomic data are lacking. To address this, we introduce CyberInfrastructure for Waterborne Antibiotic Resistance Surveillance (CIWARS), a web server configured for characterizing key AR trends from longitudinal metagenomic WBS data. CIWARS offers comprehensive profiling of ARGs and taxonomic profiling of pathogen-associated bacterial taxonomic groups, identifies potential associations of ARGs with mobile genetic elements (MGEs) and pathogen-containing taxa, and assesses resistome risk based on the co-occurrence of ARGs, MGEs, and pathogen-like sequences. Additionally, it detects anomalous AR indicators over time, aiding in identifying potential events of concern, such as the emergence of resistant strains or outbreaks. Through interactive temporal data visualization, CIWARS enables AR monitoring and can serve as a tool to inform effective and timely interventions to mitigate the spread and transmission of AR. Here, CIWARS is demonstrated using longitudinal metagenomic data from a wastewater treatment plant (WWTP) influent and effluent, but it can be extended to any environment. CIWARS provides a valuable tool to support global efforts to combat the evolution and spread of AR, while also guiding agricultural and public health efforts aimed at optimizing antibiotic use. The web server is freely available at https://***/. © 2025 Elsevier Ltd

关键词： anomaly detection antibiotic resistance (AR) AR indicator profiling longitudinal metagenomics wastewater-based surveillance

来源：评论

学校读者我要写书评

暂无评论

Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

引用

Physical Review Materials 2023年第7期7卷 073605-073605页

作者： Aya Nawano Weiwei Jin Jan Schroers Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

A coarse-grained spring network model is proposed for the prediction of the mechanical response of metallic glasses as a function of the microstructure prior to loading. This model describes the mechanical response of metallic glasses using a network of parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions of the spring network model for stress versus strain to results from numerical simulations of athermal quasistatic, uniaxial tensile deformation of Cu50Zr50 metallic glasses using Lennard-Jones (LJ) and embedded atom method (EAM) atomic interactions. We show that both the LJ and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters [ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ=0 and at large strain, and strain at fracture where σ=0], we demonstrate that the spring network model can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses.

关键词： Alloys Amorphous materials Glasses Packing & jamming problems Molecular dynamics

来源：评论

学校读者我要写书评

暂无评论

BPS2025 - Biophysical insights into allosteric modulation and inhibition of viral proteases using MD simulations

引用

Biophysical Journal 2025年第3期124卷 61a-61a页

作者： Marion Q. LoPresti Kelsie M. King Anne M. Brown Virginia Tech Blacksburg VA USA Genetics Bioinformatics and Computational Biology Program Virginia Tech Christiansburg VA USA Department of Biochemistry Virginia Tech Blacksburg VA USA

来源：评论

学校读者我要写书评

暂无评论

Continuity Equation of Left Invariant Gauge Field in Quantum Genotype Of Deltacron

SSRN

引用

SSRN 2022年

作者： Hannongbua, Supot Kanjamapornkul, Kabin Rungrotmongkol, Thanyada Department of Chemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Biocatalyst and Environmental Biotechnology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok10330 Thailand

The continuity equation for the invariant gauge field of Deltacron was investigated from the replication and recombination of Delta with Omicron. The new definition of left translation of the invariant gauge field in the quantum genotype of virus and host cell was introduced. The Yang-Mills field in genetic code is an induced curvature in the parallel transport of a unified field between hydrogen bonding between three types of biomolecules. where we defined the invariant gauge field in quantum genotype. This issue allows us to identify the Poincare duality between the nteraction between the behavior field of gene expression in parasitism state and in the curvature of connection in fiber space of Spike protein folding molecule. The Chern Simons current is the anti-self-dual state of mutation between two types of interactive behavior fields in The recombination process of Deltacron was used to plot the Yang-Mills curvature directly from the underlying genetic codes. Further analysis shows that the difference between the tensor correlation with various times of Deltacron the change slope of Omicron BA.1 to the flat curve of the network correlation and closedness centrality of amino acids in receptor binding domain of Spike protein. © 2022, The Authors. All rights reserved.

关键词： Gene expression

来源：评论

学校读者我要写书评

暂无评论

A FLOW ARTIST FOR HIGH-DIMENSIONAL CELLULAR DATA

arXiv

引用

arXiv 2023年

作者： MacDonald, Kincaid Bhaskar, Dhananjay Thampakkul, Guy Nguyen, Nhi Zhang, Joia Perlmutter, Michael Adelstein, Ian Krishnaswamy, Smita Department of Mathematics Yale University United States Department of Genetics Yale School of Medicine United States Department of Computer Science Yale University United States Department of Mathematics Pomona College United States Applied Mathematics Program Yale University United States Department of Statistics University of Washington United States Department of Mathematics Boise State University United States Computational Biology and Bioinformatics Program Yale University United States

We consider the problem of embedding point cloud data sampled from an underlying manifold with an associated flow or velocity. Such data arises in many contexts where static snapshots of dynamic entities are measured, including in high-throughput biology such as single-cell transcriptomics. Existing embedding techniques either do not utilize velocity information or embed the coordinates and velocities independently, i.e., they either impose velocities on top of an existing point embedding or embed points within a prescribed vector field. Here we present FlowArtist, a neural network that embeds points while jointly learning a vector field around the points. The combination allows FlowArtist to better separate and visualize velocity-informed structures. Our results, on toy datasets and single-cell RNA velocity data, illustrate the value of utilizing coordinate and velocity information in tandem for embedding and visualizing high-dimensional data. © 2023, CC BY.

关键词： RNA

来源：评论

学校读者我要写书评

暂无评论

Insights into the binding interactions of Macitentan to bovine serum Albumin: A Spectroscopic, electrochemical and computational study

引用

Journal of Molecular Liquids 2025年 429卷

作者： Sadak, Selenay Dindar, Çiğdem Kanbeş Kabir, Md.Zahirul Rehman, Fazal Mohamad, Saharuddin B. Yildirim, Sercan Uslu, Bengi Ankara University Faculty of Pharmacy Department of Analytical Chemistry Ankara06560 Turkey Ankara University The Graduate School of Health Sciences Ankara06110 Turkey Biochemistry Program Institute of Biological Sciences Faculty of Science University Malaya Kuala Lumpur Malaysia Faculty of Science Bioinformatics Programme Institute of Biological Sciences Malaysia Centre of Research for Computational Sciences and Informatics for Biology Bioindustry Environment Agriculture and Healthcare University of Malaya Kuala Lumpur Malaysia Karadeniz Technical University Faculty of Pharmacy Department of Analytical Chemistry Trabzon Turkey

Macitentan (MACI) is an endothelial receptor antagonist used to treat pulmonary arterial hypertension (PAH). The pharmacokinetics and therapeutic efficacy of MACI are significantly influenced by its interaction with plasma proteins, especially bovine serum albumin (BSA). In this study, spectroscopic (fluorescence and UV–visible absorption spectroscopy), electrochemical, and computational techniques were applied to explore the binding properties and interaction mechanisms between MACI and BSA. The results indicated that the MACI quenched BSA fluorescence through a static mechanism. The interaction possessed a moderate binding affinity with Ka values ranging from 1.27 × 104 to 7.25 × 104 M−1 at different temperatures. Hydrophobic forces and hydrogen bonds were identified as critical factors in stabilizing the complex based on thermodynamic parameters. The local environment of tryptophan residues in BSA was found to be altered following the addition of MACI, as revealed by synchronous and three-dimensional fluorescence spectra. The spectroscopic studies were supported by electrochemical analyses, which indicated the formation of an electro-inactive complex between MACI and BSA. From the molecular docking experiments, the most likely binding site for MACI was found to be site I of BSA. Several hydrogen bonds and hydrophobic contacts were observed during the interaction of MACI with site I of BSA. These findings provided detailed insight to understand the binding properties of MACI to BSA, which may be beneficial for medical and pharmaceutical applications in the future. © 2025 Elsevier B.V.

关键词： Hydrogen bonds

来源：评论

学校读者我要写书评

暂无评论

scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

引用

Nature communications 2025年第1期16卷 4994页

作者： Gefei Wang Jia Zhao Yingxin Lin Tianyu Liu Yize Zhao Hongyu Zhao Department of Biostatistics Yale University New Haven CT USA. Program of Computational Biology and Bioinformatics Yale University New Haven CT USA. Department of Biostatistics Yale University New Haven CT USA. hongyu.zhao@yale.edu. Program of Computational Biology and Bioinformatics Yale University New Haven CT USA. hongyu.zhao@yale.edu.

Recent advancements in single-cell technologies have enabled comprehensive characterization of cellular states through transcriptomic, epigenomic, and proteomic profiling at single-cell resolution. These technologies have significantly deepened our understanding of cell functions and disease mechanisms from various omics perspectives. As these technologies evolve rapidly and data resources expand, there is a growing need for computational methods that can integrate information from different modalities to facilitate joint analysis of single-cell multi-omics data. However, integrating single-cell omics datasets presents unique challenges due to varied feature correlations and technology-specific limitations. To address these challenges, we introduce scMODAL, a deep learning framework tailored for single-cell multi-omics data alignment using feature links. scMODAL integrates datasets with limited known positively correlated features, leveraging neural networks and generative adversarial networks to align cell embeddings and preserve feature topology. Our experiments demonstrate scMODAL's effectiveness in removing unwanted variation, preserving biological information, and accurately identifying cell subpopulations across diverse datasets. scMODAL not only advances integration tasks but also supports downstream analyses such as feature imputation and feature relationship inference, offering a robust solution for advancing single-cell multi-omics research.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Protein folding as a jamming transition

arXiv

引用

arXiv 2024年

作者： Grigas, Alex T. Liu, Zhuoyi Logan, Jack A. Shattuck, Mark D. O’Hern, Corey S. Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Proteins fold to a specific functional conformation with a densely packed hydrophobic core that controls their stability. We develop a geometric, yet all-atom model for proteins that explains the universal core packing fraction of φc = 0.55 found in experimental measurements. We show that as the hydrophobic interactions increase relative to the temperature, a novel jamming transition occurs when the core packing fraction exceeds φc. The model also recapitulates the global structure of proteins since it can accurately refold to native-like structures from partially unfolded states. © 2024, CC BY.

关键词： Proteins

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：