Quantitative Biology最新文献

Computational Systems Biology Approaches to Cellular Aging - Integrating Network Maps and Dynamical Models. 细胞老化的计算系统生物学方法-整合网络地图和动态模型。

IF 0.6 4区生物学

Quantitative Biology Pub Date : 2025-12-01 Epub Date: 2025-05-26 DOI: 10.1002/qub2.70007

Hetian Su, Nan Hao

{"title":"Computational Systems Biology Approaches to Cellular Aging - Integrating Network Maps and Dynamical Models.","authors":"Hetian Su, Nan Hao","doi":"10.1002/qub2.70007","DOIUrl":"10.1002/qub2.70007","url":null,"abstract":"Cellular aging is a multifaceted, complex process. Many genes and factors have been identified that regulate cellular aging. However, how these genes and factors interact with one another and how these interactions drive the aging processes in single cells remain largely unclear. Recently, computational systems biology has demonstrated its potential to empower aging research by providing quantitative descriptions and explanations of complex aging phenotypes, mechanistic insights into the emergent dynamic properties of regulatory networks, and testable predictions that can guide the design of new experiments and interventional strategies. In general, current complex systems approaches can be categorized into two types: (1) network maps that depict the topologies of large-scale molecular networks without detailed characterization of the dynamics of individual components and (2) dynamical models that describe the temporal behavior in a particular set of interacting factors. In this review, we discuss examples that showcase the application of these approaches to cellular aging, with a specific focus on the progress in quantifying and modeling the replicative aging of budding yeast Saccharomyces cerevisiae. We further propose potential strategies for integrating network maps and dynamical models toward a more comprehensive, mechanistic, and predictive understanding of cellular aging. Finally, we outline directions and questions in aging research where systems-level approaches may be especially powerful.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"13 4","pages":""},"PeriodicalIF":0.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12277577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144691910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Perspectives on integrating artificial intelligence and single-cell omics for cellular plasticity research. 人工智能与单细胞组学在细胞可塑性研究中的结合展望。

IF 1.4 4区生物学

Quantitative Biology Pub Date : 2025-12-01 Epub Date: 2025-04-24 DOI: 10.1002/qub2.70004

Ahmed Ghobashi, Qin Ma

{"title":"Perspectives on integrating artificial intelligence and single-cell omics for cellular plasticity research.","authors":"Ahmed Ghobashi, Qin Ma","doi":"10.1002/qub2.70004","DOIUrl":"https://doi.org/10.1002/qub2.70004","url":null,"abstract":"Cellular plasticity enables cells to dynamically adapt to environmental changes by altering their phenotype. This plasticity plays a crucial role in tissue repair and regeneration and contributes to pathological processes such as cancer metastasis. Advances in single-cell omics have significantly advanced the study of cellular states and provided new opportunities for accurate cell classification and uncovering cellular transitions. In this perspective, we emphasize integrating chromatin accessibility data and extrinsic factors, such as microenvironmental cues, with single-cell transcriptomic data to develop holistic models for identifying plastic cell states. Additionally, coupling artificial intelligence with single-cell omics offers transformative potential to address existing challenges and fill gaps in identifying and characterizing plastic cells. We envision the development of a universal plasticity metric, a standardized metric for quantifying cellular plasticity. This metric would enable consistent measurement across diverse studies, creating a unified framework that bridges fields such as developmental biology, cancer research, and regenerative medicine. Fostering innovative approaches to identifying and analyzing cellular plasticity promises not only to deepen our understanding of cellular plasticity but also to accelerate therapeutic advancements, paving the way for novel precision medicine strategies to treat complex diseases such as cancer.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"13 4","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12380408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144973469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unveiling roles of non-coding RNAs in cancer through advanced technologies. 通过先进技术揭示非编码rna在癌症中的作用。

IF 1.4 4区生物学

Quantitative Biology Pub Date : 2025-12-01 Epub Date: 2025-04-20 DOI: 10.1002/qub2.70005

Runhao Wang, Leng Han

引用次数: 0

Bioinformatics and biomedical informatics with ChatGPT: Year one review. 使用 ChatGPT 的生物信息学和生物医学信息学：一年回顾。

IF 0.6 4区生物学

Quantitative Biology Pub Date : 2024-12-01 Epub Date: 2024-06-27 DOI: 10.1002/qub2.67

Jinge Wang, Zien Cheng, Qiuming Yao, Li Liu, Dong Xu, Gangqing Hu

引用次数: 0

A comprehensive evaluation of large language models in mining gene relations and pathway knowledge. 对挖掘基因关系和路径知识的大型语言模型进行综合评估。

IF 0.6 4区生物学

Quantitative Biology Pub Date : 2024-12-01 Epub Date: 2024-06-21 DOI: 10.1002/qub2.57

Muhammad Azam, Yibo Chen, Micheal Olaolu Arowolo, Haowang Liu, Mihail Popescu, Dong Xu

{"title":"A comprehensive evaluation of large language models in mining gene relations and pathway knowledge.","authors":"Muhammad Azam, Yibo Chen, Micheal Olaolu Arowolo, Haowang Liu, Mihail Popescu, Dong Xu","doi":"10.1002/qub2.57","DOIUrl":"10.1002/qub2.57","url":null,"abstract":"Understanding complex biological pathways, including gene-gene interactions and gene regulatory networks, is critical for exploring disease mechanisms and drug development. Manual literature curation of biological pathways cannot keep up with the exponential growth of new discoveries in the literature. Large-scale language models (LLMs) trained on extensive text corpora contain rich biological information, and they can be mined as a biological knowledge graph. This study assesses 21 LLMs, including both application programming interface (API)-based models and open-source models in their capacities of retrieving biological knowledge. The evaluation focuses on predicting gene regulatory relations (activation, inhibition, and phosphorylation) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway components. Results indicated a significant disparity in model performance. API-based models GPT-4 and Claude-Pro showed superior performance, with an F1 score of 0.4448 and 0.4386 for the gene regulatory relation prediction, and a Jaccard similarity index of 0.2778 and 0.2657 for the KEGG pathway prediction, respectively. Open-source models lagged behind their API-based counterparts, whereas Falcon-180b and llama2-7b had the highest F1 scores of 0.2787 and 0.1923 in gene regulatory relations, respectively. The KEGG pathway recognition had a Jaccard similarity index of 0.2237 for Falcon-180b and 0.2207 for llama2-7b. Our study suggests that LLMs are informative in gene network analysis and pathway mapping, but their effectiveness varies, necessitating careful model selection. This work also provides a case study and insight into using LLMs das knowledge graphs. Our code is publicly available at the website of GitHub (Muh-aza).","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"12 4","pages":"360-374"},"PeriodicalIF":0.6,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11446478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gene regulatory network inference based on causal discovery integrating with graph neural network 基于因果发现的基因调控网络推断与图神经网络的整合

IF 3.1 4区生物学

Quantitative Biology Pub Date : 2023-12-01 DOI: 10.1002/qub2.26

Ke Feng, Hongyang Jiang, Chaoyi Yin, Huiyan Sun

{"title":"Gene regulatory network inference based on causal discovery integrating with graph neural network","authors":"Ke Feng, Hongyang Jiang, Chaoyi Yin, Huiyan Sun","doi":"10.1002/qub2.26","DOIUrl":"https://doi.org/10.1002/qub2.26","url":null,"abstract":"Gene regulatory network (GRN) inference from gene expression data is a significant approach to understanding aspects of the biological system. Compared with generalized correlation‐based methods, causality‐inspired ones seem more rational to infer regulatory relationships. We propose GRINCD, a novel GRN inference framework empowered by graph representation learning and causal asymmetric learning, considering both linear and non‐linear regulatory relationships. First, high‐quality representation of each gene is generated using graph neural network. Then, we apply the additive noise model to predict the causal regulation of each regulator‐target pair. Additionally, we design two channels and finally assemble them for robust prediction. Through comprehensive comparisons of our framework with state‐of‐the‐art methods based on different principles on numerous datasets of diverse types and scales, the experimental results show that our framework achieves superior or comparable performance under various evaluation metrics. Our work provides a new clue for constructing GRNs, and our proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"458 ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139022894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Reorganizing heterogeneous information from host–microbe interaction reveals innate associations among samples 重组来自宿主-微生物相互作用的异质信息，揭示样本间的先天联系

IF 3.1 4区生物学

Quantitative Biology Pub Date : 2023-11-29 DOI: 10.1002/qub2.25

Hongfei Cui

{"title":"Reorganizing heterogeneous information from host–microbe interaction reveals innate associations among samples","authors":"Hongfei Cui","doi":"10.1002/qub2.25","DOIUrl":"https://doi.org/10.1002/qub2.25","url":null,"abstract":"The information on host–microbe interactions contained in the operational taxonomic unit (OTU) abundance table can serve as a clue to understanding the biological traits of OTUs and samples. Some studies have inferred the taxonomies or functions of OTUs by constructing co‐occurrence networks, but co‐occurrence networks can only encompass a small fraction of all OTUs due to the high sparsity of the OTU table. There is a lack of studies that intensively explore and use the information on sample‐OTU interactions. This study constructed a sample‐OTU heterogeneous information network and represented the nodes in the network through the heterogeneous graph embedding method to form the OTU space and sample space. Taking advantage of the represented OTU and sample vectors combined with the original OTU abundance information, an Integrated Model of Embedded Taxonomies and Abundance (IMETA) was proposed for predicting sample attributes, such as phenotypes and individual diet habits. Both the OTU space and sample space contain reasonable biological or medical semantic information, and the IMETA using embedded OTU and sample vectors can have stable and good performance in the sample classification tasks. This suggests that the embedding representation based on the sample‐OTU heterogeneous information network can provide more useful information for understanding microbiome samples. This study conducted quantified representations of the biological characteristics within the OTUs and samples, which is a good attempt to increase the utilization rate of information in the OTU abundance table, and it promotes a deeper understanding of the underlying knowledge of human microbiome.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"16 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Toward atomistic models of intact severe acute respiratory syndrome coronavirus 2 via Martini coarse‐grained molecular dynamics simulations 通过马蒂尼粗粒度分子动力学模拟建立完整的严重急性呼吸系统综合征冠状病毒 2 的原子模型

IF 3.1 4区生物学

Quantitative Biology Pub Date : 2023-11-28 DOI: 10.1002/qub2.20

Dali Wang, Jiaxuan Li, Lei Wang, Yipeng Cao, Bo Kang, Xiangfei Meng, Sai Li, Chen Song

{"title":"Toward atomistic models of intact severe acute respiratory syndrome coronavirus 2 via Martini coarse‐grained molecular dynamics simulations","authors":"Dali Wang, Jiaxuan Li, Lei Wang, Yipeng Cao, Bo Kang, Xiangfei Meng, Sai Li, Chen Song","doi":"10.1002/qub2.20","DOIUrl":"https://doi.org/10.1002/qub2.20","url":null,"abstract":"The causative pathogen of coronavirus disease 2019 (COVID‐19), severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), is an enveloped virus assembled by a lipid envelope and multiple structural proteins. In this study, by integrating experimental data, structural modeling, as well as coarse‐grained and all‐atom molecular dynamics simulations, we constructed multiscale models of SARS‐CoV‐2. Our 500‐ns coarse‐grained simulation of the intact virion allowed us to investigate the dynamic behavior of the membrane‐embedded proteins and the surrounding lipid molecules in situ. Our results indicated that the membrane‐embedded proteins are highly dynamic, and certain types of lipids exhibit various binding preferences to specific sites of the membrane‐embedded proteins. The equilibrated virion model was transformed into atomic resolution, which provided a 3D structure for scientific demonstration and can serve as a framework for future exascale all‐atom molecular dynamics (MD) simulations. A short all‐atom molecular dynamics simulation of 255 ps was conducted as a preliminary test for large‐scale simulations of this complex system.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"20 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139223234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Theoretical perspective on synthetic man‐made life: Learning from the origin of life 人造合成生命的理论视角：向生命起源学习

IF 3.1 4区生物学

Quantitative Biology Pub Date : 2023-11-27 DOI: 10.1002/qub2.22

Lu Peng, Zecheng Zhang, Xianyi Wang, Weiyi Qiu, Liqian Zhou, Hui Xiao, Chunxiuzi Liu, Shaohua Tang, Zhiwei Qin, Jiakun Jiang, Zengru Di, Yu Liu

{"title":"Theoretical perspective on synthetic man‐made life: Learning from the origin of life","authors":"Lu Peng, Zecheng Zhang, Xianyi Wang, Weiyi Qiu, Liqian Zhou, Hui Xiao, Chunxiuzi Liu, Shaohua Tang, Zhiwei Qin, Jiakun Jiang, Zengru Di, Yu Liu","doi":"10.1002/qub2.22","DOIUrl":"https://doi.org/10.1002/qub2.22","url":null,"abstract":"Creating a man‐made life in the laboratory is one of life science’s most intriguing yet challenging problems. Advances in synthetic biology and related theories, particularly those related to the origin of life, have laid the groundwork for further exploration and understanding in this field of artificial life or man‐made life. But there remains a wealth of quantitative mathematical models and tools that have yet to be applied to this area. In this paper, we review the two main approaches often employed in the field of man‐made life: the top‐down approach that reduces the complexity of extant and existing living systems and the bottom‐up approach that integrates well‐defined components, by introducing the theoretical basis, recent advances, and their limitations. We then argue for another possible approach, namely “bottom‐up from the origin of life”: Starting with the establishment of autocatalytic chemical reaction networks that employ physical boundaries as the initial compartments, then designing directed evolutionary systems, with the expectation that independent compartments will eventually emerge so that the system becomes free‐living. This approach is actually analogous to the process of how life originated. With this paper, we aim to stimulate the interest of synthetic biologists and experimentalists to consider a more theoretical perspective, and to promote the communication between the origin of life community and the synthetic man‐made life community.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"30 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139231000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Conductive proteins‐based extracellular electron transfer of electroactive microorganisms 基于导电蛋白质的电活性微生物胞外电子转移

IF 3.1 4区生物学

Quantitative Biology Pub Date : 2023-11-27 DOI: 10.1002/qub2.24

Junqi Zhang, Zixuan You, Dingyuan Liu, Rui Tang, Chao Zhao, Yingxiu Cao, Feng Li, Hao-Qing Song

{"title":"Conductive proteins‐based extracellular electron transfer of electroactive microorganisms","authors":"Junqi Zhang, Zixuan You, Dingyuan Liu, Rui Tang, Chao Zhao, Yingxiu Cao, Feng Li, Hao-Qing Song","doi":"10.1002/qub2.24","DOIUrl":"https://doi.org/10.1002/qub2.24","url":null,"abstract":"Electroactive microorganisms (EAMs) could utilize extracellular electron transfer (EET) pathways to exchange electrons and energy with their external surroundings. Conductive cytochrome proteins and nanowires play crucial roles in controlling electron transfer rate from cytosol to extracellular electrode. Many previous studies elucidated how the c‐type cytochrome proteins and conductive nanowires are synthesized, assembled, and engineered to manipulate the EET rate, and quantified the kinetic processes of electron generation and EET. Here, we firstly overview the electron transfer pathways of EAMs and quantify the kinetic parameters that dictating intracellular electron production and EET. Secondly, we systematically review the structure, conductivity mechanisms, and engineering strategies to manipulate conductive cytochromes and nanowire in EAMs. Lastly, we outlook potential directions for future research in cytochromes and conductive nanowires for enhanced electron transfer. This article reviews the quantitative kinetics of intracellular electron production and EET, and the contribution of engineered c‐type cytochromes and conductive nanowire in enhancing the EET rate, which lay the foundation for enhancing electron transfer capacity of EAMs.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"61 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139228917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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