Nucleic Acids Research最新文献_第9页

Onkopus: precise interpretation and prioritization of sequence variants for biomedical research and precision medicine. Onkopus：生物医学研究和精准医学序列变异的精确解释和优先排序。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf376

Nadine S Kurz,Kevin Kornrumpf,Tim Tucholski,Klara Drofenik,Alexander König,Tim Beißbarth,Jürgen Dönitz

{"title":"Onkopus: precise interpretation and prioritization of sequence variants for biomedical research and precision medicine.","authors":"Nadine S Kurz,Kevin Kornrumpf,Tim Tucholski,Klara Drofenik,Alexander König,Tim Beißbarth,Jürgen Dönitz","doi":"10.1093/nar/gkaf376","DOIUrl":"https://doi.org/10.1093/nar/gkaf376","url":null,"abstract":"One of the major challenges in precision oncology is the identification of pathogenic, actionable variants and the selection of personalized treatments. We present Onkopus, a variant interpretation framework based on a modular architecture, for interpreting and prioritizing genetic alterations in cancer patients. A multitude of tools and databases are integrated into Onkopus to provide a comprehensive overview about the consequences of a variant, each with its own semantic, including pathogenicity predictions, allele frequency, biochemical and protein features, and therapeutic options. We present the characteristics of variants and personalized therapies in a clear and concise form, supported by interactive plots. To support the interpretation of variants of unknown significance (VUS), we present a protein analysis based on protein structures, which allows variants to be analyzed within the context of the entire protein, thereby serving as a starting point for understanding the underlying causes of variant pathogenicity. Onkopus has the potential to significantly enhance variant interpretation and the selection of actionable variants for identifying new targets, drug screens, drug testing using organoids, or personalized treatments in molecular tumor boards. We provide a free public instance of Onkopus at https://mtb.bioinf.med.uni-goettingen.de/onkopus.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"8 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ASOptimizer: optimizing chemical diversity of antisense oligonucleotides through deep learning. ASOptimizer：通过深度学习优化反义寡核苷酸的化学多样性。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf392

Seokjun Kang,Daehwan Lee,Gyeongjo Hwang,Kiwon Lee,Mingeun Kang

引用次数: 0

CRISPR-BEasy: a free web-based service for designing sgRNA tiling libraries for CRISPR-dependent base editing screens. CRISPR-BEasy：一个免费的基于web的服务，用于为crispr依赖的碱基编辑屏幕设计sgRNA平铺库。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf382

Vincent Chapdelaine-Trépanier,Shamika Shenoy,Wardah Masud,Amisha Minju-Op,Marie-Anne Bérubé,Sebastian Schönherr,Lukas Forer,Amélie Fradet-Turcotte,Daniel Taliun,Raquel Cuella-Martin

{"title":"CRISPR-BEasy: a free web-based service for designing sgRNA tiling libraries for CRISPR-dependent base editing screens.","authors":"Vincent Chapdelaine-Trépanier,Shamika Shenoy,Wardah Masud,Amisha Minju-Op,Marie-Anne Bérubé,Sebastian Schönherr,Lukas Forer,Amélie Fradet-Turcotte,Daniel Taliun,Raquel Cuella-Martin","doi":"10.1093/nar/gkaf382","DOIUrl":"https://doi.org/10.1093/nar/gkaf382","url":null,"abstract":"CRISPR-dependent base editing (BE) enables the modeling and correction of genetic mutations at single-base resolution. Base editing screens, where point mutations are queried en masse, are powerful tools to systematically draw genotype-phenotype associations and characterise the function of genes and other genomic elements. However, the lack of user-friendly web-based tools for designing base editing screens can hinder broad technology adoption. Here, we introduce CRISPR-BEasy (https://crispr-beasy.cerc-genomic-medicine.ca), a free, automated web-based server that streamlines the creation of single guide (sg)RNA tiling libraries for base editing screens. Researchers can provide their genes or genomic features of interest, their base editors of choice, and target sequences to act as positive and negative controls. The server designs and annotates sgRNA libraries by integrating custom code with publicly available tools such as crisprVerse and Ensembl's Variant Effect Predictor. CRISPR-BEasy provides downloadable results, including sgRNA on/off-target scores, predicted mutational outcomes per base editor, and intuitive interactive visualizations for data quality assessment. CRISPR-BEasy also provides a separate tool that assembles sgRNA libraries into oligonucleotides for cloning following the detailed protocol documented in the searchable web server manual. Together, CRISPR-BEasy ensures the seamless design of cloning-ready sgRNA libraries, seeking to democratise access to base editing screening technologies.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"3 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LIGYSIS-web: a resource for the analysis of protein-ligand binding sites. LIGYSIS-web：一个分析蛋白质配体结合位点的资源。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf411

Javier S Utgés,Stuart A MacGowan,Geoffrey J Barton

{"title":"LIGYSIS-web: a resource for the analysis of protein-ligand binding sites.","authors":"Javier S Utgés,Stuart A MacGowan,Geoffrey J Barton","doi":"10.1093/nar/gkaf411","DOIUrl":"https://doi.org/10.1093/nar/gkaf411","url":null,"abstract":"LIGYSIS-web is a free website accessible to all users without any login requirement for the analysis of protein-ligand binding sites. LIGYSIS-web hosts a database of 65,000 protein-ligand binding sites across 25,000 proteins. LIGYSIS sites are defined by aggregating unique relevant protein-ligand interfaces across different biological assemblies of the same protein deposited on the PDBe. Additionally, users can upload their own structures in PDB or mmCIF format for analysis and subsequent visualisation and download. Ligand sites are characterised using evolutionary divergence from a multiple sequence alignment, human missense genetic variation from gnomAD and relative solvent accessibility to obtain accessibility-based cluster labels and scores indicating likelihood of function. These results are displayed in the LIGYSIS web server, a Python Flask web application with a JavaScript frontend employing Jinja and jQuery to link the 3Dmol.js structure viewer with dynamic tables and Chart.js graphs in an interactive manner. LIGYSIS-web is available at https://www.compbio.dundee.ac.uk/ligysis/, whilst the source code for the analysis pipelines and web application can be accessed at https://github.com/bartongroup/LIGYSIS, https://github.com/bartongroup/LIGYSIS-custom and https://github.com/bartongroup/LIGYSIS-web, respectively.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"53 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CellHit: a web server to predict and analyze cancer patients' drug responsiveness. CellHit：一个预测和分析癌症患者药物反应的网络服务器。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf414

Francesco Carli,Natalia De Oliveira Rosa,Simon Blotas,Pierluigi Di Chiaro,Luisa Bisceglia,Mariangela Morelli,Francesca Lessi,Anna Luisa Di Stefano,Chiara Maria Mazzanti,Gioacchino Natoli,Francesco Raimondi

{"title":"CellHit: a web server to predict and analyze cancer patients' drug responsiveness.","authors":"Francesco Carli,Natalia De Oliveira Rosa,Simon Blotas,Pierluigi Di Chiaro,Luisa Bisceglia,Mariangela Morelli,Francesca Lessi,Anna Luisa Di Stefano,Chiara Maria Mazzanti,Gioacchino Natoli,Francesco Raimondi","doi":"10.1093/nar/gkaf414","DOIUrl":"https://doi.org/10.1093/nar/gkaf414","url":null,"abstract":"We present the CellHit web server (https://cellhit.bioinfolab.sns.it/), a web-based platform designed to predict and analyze cancer patients' responsiveness to drugs using transcriptomic data. By leveraging extensive pharmacogenomics datasets from the Genomics of Drug Sensitivity in Cancer v1 and v2 (GDSC) and Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) and transcriptomic data from the Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas Program (TCGA). CellHit integrates a computational pipeline for preprocessing, gene imputation, and robust alignment between patient and cell line transcriptomic data with pre-trained SOTA models for drug sensitivity prediction. The pipeline employs batch correction, enhanced Celligner methodology, and Parametric UMAP for stable and actionable alignment. The intuitive interface requires no programming expertise, offering interactive visualizations, including low-dimensional embeddings and drug sensitivity heatmaps for the input transcriptomic samples. Results feature contextual metadata, SHAP-based feature importance, and transcriptomic neighbors from reference datasets, simplifying interpretation and hypothesis generation. CellHit provides precomputed predictions across TCGA samples and offers the ability to run custom analyses online on input samples, democratizing precision oncology by enabling rapid, interpretable predictions accessible the research community.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"12388 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transcription factors form a ternary complex with NIPBL/MAU2 to localize cohesin at enhancers 转录因子与NIPBL/MAU2形成三元复合物，以定位内聚蛋白增强子

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf415

Gregory Fettweis, Kaustubh Wagh, Diana A Stavreva, Alba Jiménez-Panizo, Sohyoung Kim, Michelle Lion, Andrea Alegre-Martí, Lorenzo Rinaldi, Thomas A Johnson, Elise Gilson, Manan Krishnamurthy, Li Wang, David A Ball, Tatiana S Karpova, Arpita Upadhyaya, Didier Vertommen, Juan Fernández Recio, Eva Estébanez-Perpiñá, Franck Dequiedt, Gordon L Hager

{"title":"Transcription factors form a ternary complex with NIPBL/MAU2 to localize cohesin at enhancers","authors":"Gregory Fettweis, Kaustubh Wagh, Diana A Stavreva, Alba Jiménez-Panizo, Sohyoung Kim, Michelle Lion, Andrea Alegre-Martí, Lorenzo Rinaldi, Thomas A Johnson, Elise Gilson, Manan Krishnamurthy, Li Wang, David A Ball, Tatiana S Karpova, Arpita Upadhyaya, Didier Vertommen, Juan Fernández Recio, Eva Estébanez-Perpiñá, Franck Dequiedt, Gordon L Hager","doi":"10.1093/nar/gkaf415","DOIUrl":"https://doi.org/10.1093/nar/gkaf415","url":null,"abstract":"While the cohesin complex is a key player in genome architecture, how it localizes to specific chromatin sites is not understood. Recently, we and others have proposed that direct interactions with transcription factors lead to the localization of the cohesin-loader complex (NIPBL/MAU2) within enhancers. Here, we identify two clusters of LxxLL motifs within the NIPBL sequence that regulate NIPBL dynamics, interactome, and NIPBL-dependent transcriptional programs. One of these clusters interacts with MAU2 and is necessary for the maintenance of the NIPBL–MAU2 heterodimer. The second cluster binds specifically to the ligand-binding domains of steroid receptors. For the glucocorticoid receptor (GR), we examine in detail its interaction surfaces with NIPBL and MAU2. Using AlphaFold2 and molecular docking algorithms, we uncover a GR–NIPBL–MAU2 ternary complex and describe its importance in GR-dependent gene regulation. Finally, we show that multiple transcription factors interact with NIPBL–MAU2, likely using interfaces other than those characterized for GR.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"11 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CapBuild: a cloud-native tool for adeno-associated virus capsid engineering. CapBuild：用于腺相关病毒衣壳工程的云原生工具。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf422

Anne H Klein,Michael J Kuiper,Mark Burgess,Anuradha Wickramarachchi,Yatish Jain,Denis C Bauer,Laurence Wilson

{"title":"CapBuild: a cloud-native tool for adeno-associated virus capsid engineering.","authors":"Anne H Klein,Michael J Kuiper,Mark Burgess,Anuradha Wickramarachchi,Yatish Jain,Denis C Bauer,Laurence Wilson","doi":"10.1093/nar/gkaf422","DOIUrl":"https://doi.org/10.1093/nar/gkaf422","url":null,"abstract":"Adeno-associated virus (AAV) capsid engineering is essential for advancing gene therapy but remains limited by structural complexity and computational constraints. To address these challenges, we developed CapBuild, a cloud-native web server that streamlines AAV capsid prediction, assembly and engineering. CapBuild provides two distinct workflows: a PDB-based pipeline for assembling complete capsids from structural files and a modelling pipeline that constructs capsids from protein sequences via SWISS-MODEL. The platform incorporates icosahedral symmetry through transformation matrices and features an integrated mutation modeller for visualising site-specific mutations across the entire capsid. Additionally, its amino acid localisation tool maps exposed and buried residues, facilitating rational design. Benchmarking against crystal structures demonstrates high structural accuracy, with consistently low RMSD values (0-0.89 Å) and high GDT scores (89.4-100%) across multiple AAV serotypes. CapBuild's interactive visualisation interface, powered by Mol*, enables in-depth structural analysis, making capsid engineering more accessible to researchers. By reducing technical barriers and automating complex modelling tasks, CapBuild facilitates early-stage AAV capsid design, enabling researchers to rationally explore and visualise structural variants for potential use. CapBuild is available at https://capbuild.csiro.au/.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"124 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery. LitSense 2.0：人工智能生物医学信息检索，具有句子和段落级别的知识发现。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-16 DOI: 10.1093/nar/gkaf417

Lana Yeganova,Won Kim,Shubo Tian,Donald C Comeau,W John Wilbur,Zhiyong Lu

{"title":"LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery.","authors":"Lana Yeganova,Won Kim,Shubo Tian,Donald C Comeau,W John Wilbur,Zhiyong Lu","doi":"10.1093/nar/gkaf417","DOIUrl":"https://doi.org/10.1093/nar/gkaf417","url":null,"abstract":"LitSense 2.0 (https://www.ncbi.nlm.nih.gov/research/litsense2/) is an advanced biomedical search system enhanced with dense vector semantic retrieval, designed for accessing literature on sentence and paragraph levels. It provides unified access to 38 million PubMed abstracts and 6.6 million full-length articles in the PubMed Central (PMC) Open Access subset, encompassing 1.4 billion sentences and ∼300 million paragraphs, and is updated weekly. Compared to PubMed and PMC, the primary platforms for biomedical information search, LitSense offers cross-platform functionality by searching seamlessly across both PubMed and PMC and returning relevant results at a more granular level. Building on the success of the original LitSense launched in 2018, LitSense 2.0 introduces two major enhancements. The first is the addition of paragraph-level search: users can now choose to search either against sentences or against paragraphs. The second is improved retrieval accuracy via a state-of-the-art biomedical text encoder, ensuring more reliable identification of relevant results across the entire biomedical literature.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"14 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

M1CR0B1AL1Z3R 2.0: an enhanced web server for comparative analysis of bacterial genomes at scale. M1CR0B1AL1Z3R 2.0：用于大规模细菌基因组比较分析的增强web服务器。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-14 DOI: 10.1093/nar/gkaf413

Yair Shimony,Edo Dotan,Elya Wygoda,Naama Wagner,Iris Lyubman,Noa Ecker,Gianna Durante,Gal Mishan,Jeff H Chang,Oren Avram,Tal Pupko

{"title":"M1CR0B1AL1Z3R 2.0: an enhanced web server for comparative analysis of bacterial genomes at scale.","authors":"Yair Shimony,Edo Dotan,Elya Wygoda,Naama Wagner,Iris Lyubman,Noa Ecker,Gianna Durante,Gal Mishan,Jeff H Chang,Oren Avram,Tal Pupko","doi":"10.1093/nar/gkaf413","DOIUrl":"https://doi.org/10.1093/nar/gkaf413","url":null,"abstract":"Large-scale analyses of bacterial genomic datasets contribute to the comprehensive characterization of complex microbial dynamics among different strains and species. Such analyses often include open reading frame extraction, orthogroup inference, phylogeny reconstruction, and functional annotation of proteins. We have previously developed the M1CR0B1AL1Z3R web server, a \"one-stop shop\" for conducting comparative analyses of microbial genomes. Here, we present M1CR0B1AL1Z3R 2.0, an enhanced version that includes a new user-friendly web interface and an improved, optimized, and more versatile pipeline. The following features were added: (i) a computationally efficient inference of orthogroups, which allows the analysis of up to 2000 bacterial genomes; (ii) genome completeness analysis; (iii) lists of orphan genes per genome; (iv) genome numeric representation that allows detecting genomic rearrangement events; (v) codon bias analysis; (vi) annotation of orthogroups with KEGG Orthology numbers; and (vii) a map of pairwise average nucleotide identity values. M1CR0B1AL1Z3R 2.0 is freely available at https://microbializer.tau.ac.il/.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"27 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143945480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation. DEMO-EMol：通过将链组装与图谱分割耦合，从低温电镜图谱中建模蛋白质核酸复合物结构。

IF 14.9 2区生物学

Nucleic Acids Research Pub Date : 2025-05-14 DOI: 10.1093/nar/gkaf416

Ziying Zhang,Liang Xu,Shuai Zhang,Chunxiang Peng,Guijun Zhang,Xiaogen Zhou

{"title":"DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation.","authors":"Ziying Zhang,Liang Xu,Shuai Zhang,Chunxiang Peng,Guijun Zhang,Xiaogen Zhou","doi":"10.1093/nar/gkaf416","DOIUrl":"https://doi.org/10.1093/nar/gkaf416","url":null,"abstract":"Atomic structure modeling is a crucial step in determining the structures of protein complexes using cryo-electron microscopy (cryo-EM). This work introduces DEMO-EMol, an improved server that integrates deep learning-based map segmentation and chain fitting to accurately assemble protein-nucleic acid (NA) complex structures from cryo-EM density maps. Starting from a density map and independently modeled chain structures, DEMO-EMol first segments protein and NA regions from the density map using deep learning. The overall complex is then assembled by fitting protein and NA chain models into their respective segmented maps, followed by domain-level fitting and optimization for protein chains. The output of DEMO-EMol includes the final assembled complex model along with overall and residue-level quality assessments. DEMO-EMol was evaluated on a comprehensive benchmark set of cryo-EM maps with resolutions ranging from 1.96 to 12.77 Å, and the results demonstrated its superior performance over the state-of-the-art methods for both protein-NA and protein-protein complex modeling. The DEMO-EMol web server is freely accessible at https://zhanggroup.org/DEMO-EMol/.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"29 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143945481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0