Genomics, proteomics & bioinformatics最新文献_第4页

HumanTestisDB: A Comprehensive Atlas of Testicular Transcriptomics and Cellular Interactions. humantestsdb：睾丸转录组学和细胞相互作用的综合图谱。

Genomics, proteomics & bioinformatics Pub Date : 2025-03-05 DOI: 10.1093/gpbjnl/qzaf015

Mengjie Wang, Laihua Li, Qing Cheng, Hao Zhang, Zhaode Liu, Yiqiang Cui, Jiahao Sha, Yan Yuan

{"title":"HumanTestisDB: A Comprehensive Atlas of Testicular Transcriptomics and Cellular Interactions.","authors":"Mengjie Wang, Laihua Li, Qing Cheng, Hao Zhang, Zhaode Liu, Yiqiang Cui, Jiahao Sha, Yan Yuan","doi":"10.1093/gpbjnl/qzaf015","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf015","url":null,"abstract":"Advances in single-cell technology have enabled the detailed mapping of testicular cell transcriptomes, which is essential for understanding spermatogenesis. However, the fragmented nature of age-specific data from various literature sources has hindered comprehensive analysis. To overcome this, the Human Testis Database (HumanTestisDB) was developed, consolidating multiple human testicular sequencing datasets to address this limitation. Through extensive investigation, 38 unique cell types were identified, providing a detailed perspective on cellular variety. Furthermore, the database systematically categorizes samples into eight developmental stages, offering a structured framework to comprehend the temporal dynamics of testicular development. Each stage features comprehensive maps of cell-cell interactions, elucidating the complex communication network inside the testicular microenvironment at particular developmental stages. Moreover, by facilitating comparisons of interactions among various cell types at different stages, the database permits examining alterations that transpire during critical transitions in spermatogenesis. HumanTestisDB, available at https://shalab.njmu.edu.cn/humantestisdb, offers vital insights into testicular transcriptomics and interactions, serving as an essential resource for advancing research in reproductive biology.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biological Data Resources and Machine Learning Frameworks for Hematology Research. 血液学研究的生物数据资源和机器学习框架。

Genomics, proteomics & bioinformatics Pub Date : 2025-03-04 DOI: 10.1093/gpbjnl/qzaf021

Ying Yi, Yongfei Hu, Juanjuan Kang, Qifa Liu, Yan Huang, Dong Wang

引用次数: 0

Single-cell Atlas of Developing Mouse Palates Reveals Cellular and Molecular Transitions in Periderm Cell Fate. 发育中的小鼠上颚单细胞图谱揭示了外周细胞命运的细胞和分子转变。

Genomics, proteomics & bioinformatics Pub Date : 2025-03-04 DOI: 10.1093/gpbjnl/qzaf013

Wenbin Huang, Zhenwei Qian, Jieni Zhang, Yi Ding, Bin Wang, Jiuxiang Lin, Xiannian Zhang, Huaxiang Zhao, Feng Chen

{"title":"Single-cell Atlas of Developing Mouse Palates Reveals Cellular and Molecular Transitions in Periderm Cell Fate.","authors":"Wenbin Huang, Zhenwei Qian, Jieni Zhang, Yi Ding, Bin Wang, Jiuxiang Lin, Xiannian Zhang, Huaxiang Zhao, Feng Chen","doi":"10.1093/gpbjnl/qzaf013","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf013","url":null,"abstract":"Cleft palate is one of the most common congenital craniofacial disorders that affects children's appearance and oral functions. Investigating the transcriptomics during palatogenesis is crucial for comprehending the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid-palatogenesis and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here we explored the single-cell landscape of mouse developing palates from embryonic day (E) 10.5 to E16.5. We systematically depicted the single-cell transcriptomics of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identified four subclusters of palatal periderm and constructed two distinct trajectories of cell fates for periderm cells. Our findings reveal that claudin-family coding genes and Arhgap29 play a role in the non-stick function of the periderm before the palatal shelves contact, and Pitx2 mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrated that epithelial-mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PhaSeDis: A Manually Curated Database of Phase Separation-Disease Associations and Corresponding Small Molecules. PhaSeDis：一个人工整理的相分离-疾病关联和相应小分子数据库。

Genomics, proteomics & bioinformatics Pub Date : 2025-03-04 DOI: 10.1093/gpbjnl/qzaf014

Taoyu Chen, Guoguo Tang, Tianhao Li, Zhining Yanghong, Chao Hou, Zezhou Du, Kaiqiang You, Liwei Ma, Tingting Li

{"title":"PhaSeDis: A Manually Curated Database of Phase Separation-Disease Associations and Corresponding Small Molecules.","authors":"Taoyu Chen, Guoguo Tang, Tianhao Li, Zhining Yanghong, Chao Hou, Zezhou Du, Kaiqiang You, Liwei Ma, Tingting Li","doi":"10.1093/gpbjnl/qzaf014","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf014","url":null,"abstract":"Biomacromolecules form membraneless organelles through liquid-liquid phase separation in order to regulate the efficiency of particular biochemical reactions. Dysregulation of phase separation might result in pathological condensation or sequestration of biomolecules, leading to diseases. Thus, phase separation and phase separating factors may serve as drug targets for disease treatment. Nevertheless, such associations have not yet been integrated into phase separation related databases. Therefore, based on MloDisDB, a database for membraneless organelle factor-disease association previously developed by our lab, we constructed PhaSeDis, the phase separation-disease association database. We increased the number of phase separation entries from 52 to 185, and supplemented the evidence provided by the original article verifying the phase separation nature of the factors. Moreover, we included the information of interacting small molecules with low-throughput or high-throughput evidence that might serve as potential drugs for phase separation entries. PhaSeDis strives to offer comprehensive descriptions of each entry, elucidating how phase separating factors induce pathological conditions via phase separation and the mechanisms by which small molecules intervene. We believe that PhaSeDis would be very important in the application of phase separation regulation in treating related diseases. PhaSeDis is available at http://mlodis.phasep.pro.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Developmental Gene Expression Atlas Reveals Novel Biological Basis of Complex Phenotypes in Sheep. 发育基因表达图谱揭示绵羊复杂表型的新生物学基础

Genomics, proteomics & bioinformatics Pub Date : 2025-03-04 DOI: 10.1093/gpbjnl/qzaf020

Bingru Zhao, Hanpeng Luo, Xuefeng Fu, Guoming Zhang, Emily L Clark, Feng Wang, Brian Paul Dalrymple, V Hutton Oddy, Philip E Vercoe, Cuiling Wu, George E Liu, Cong-Jun Li, Ruidong Xiang, Kechuan Tian, Yanli Zhang, Lingzhao Fang

{"title":"A Developmental Gene Expression Atlas Reveals Novel Biological Basis of Complex Phenotypes in Sheep.","authors":"Bingru Zhao, Hanpeng Luo, Xuefeng Fu, Guoming Zhang, Emily L Clark, Feng Wang, Brian Paul Dalrymple, V Hutton Oddy, Philip E Vercoe, Cuiling Wu, George E Liu, Cong-Jun Li, Ruidong Xiang, Kechuan Tian, Yanli Zhang, Lingzhao Fang","doi":"10.1093/gpbjnl/qzaf020","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf020","url":null,"abstract":"Sheep (Ovis aries) represents one of the most important livestock species for animal protein and wool production worldwide. However, little is known about the genetic and biological basis of ovine phenotypes, particularly for those of high economic value and environmental impact. Here, by integrating 1413 RNA-seq samples from 51 distinct tissues across 14 developmental time points, representing early prenatal, late prenatal, neonate, lamb, juvenile, adult, and elderly stages, we built a high-resolution developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. When harnessing this resource for interpreting genetic associations of 48 monogenetic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birth weight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating GWAS fine-mapping results and the sheep dGEA, we proposed several candidate genes for complex traits in sheep, such as SOX9 for MSL, GNRHR for litter size at birth, and PRKDC for live weight. These results provide novel insights into the developmental and molecular architecture underlying ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LigExtract: Large-scale Automated Identification of Ligands from Protein Structures in the Protein Data Bank. LigExtract：在蛋白质数据库中从蛋白质结构中大规模自动识别配体。

Genomics, proteomics & bioinformatics Pub Date : 2025-02-28 DOI: 10.1093/gpbjnl/qzaf018

Natália Aniceto, Nuno Martinho, Ismael Rufino, Rita C Guedes

{"title":"LigExtract: Large-scale Automated Identification of Ligands from Protein Structures in the Protein Data Bank.","authors":"Natália Aniceto, Nuno Martinho, Ismael Rufino, Rita C Guedes","doi":"10.1093/gpbjnl/qzaf018","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf018","url":null,"abstract":"The Protein Data Bank is an ever-growing database of 3D macromolecular structures that has become a crucial resource for the drug discovery process. Exploring complexed proteins and accessing the ligands in these proteins is paramount to help researchers understand biological processes and design new compounds of pharmaceutical interest. However, currently available tools to perform large-scale ligand identification do not address many of the more complex ways in which ligands are stored and represented in PDB structures. Therefore, a new tool called LigExtract was specifically developed for the large-scale processing of PDB structures and the identification of their ligands. This is a fully open-source tool available to the scientific community, designed to provide end-to-end processing whereby the user simply provides a list of UniProt IDs and LigExtract returns a list of ligands, their individual PDB files, a PDB file of the protein chains engaged with the ligand and a series of log files that inform the user of the decisions made during the ligand extraction process as well as potential flagging of additional scenarios that might have to be considered during any follow-up use of the processed files (e.g., ligands covalently bound to the protein). LigExtract is available, open-source, on GitHub (https://github.com/comp-medchem/LigExtract).","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis. 人工智能驱动的生物医学多模态数据融合与分析中的挑战。

Genomics, proteomics & bioinformatics Pub Date : 2025-02-27 DOI: 10.1093/gpbjnl/qzaf011

Junwei Liu, Xiaoping Cen, Chenxin Yi, Feng-Ao Wang, Junxiang Ding, Jinyu Cheng, Qinhua Wu, Baowen Gai, Yiwen Zhou, Ruikun He, Feng Gao, Yixue Li

{"title":"Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis.","authors":"Junwei Liu, Xiaoping Cen, Chenxin Yi, Feng-Ao Wang, Junxiang Ding, Jinyu Cheng, Qinhua Wu, Baowen Gai, Yiwen Zhou, Ruikun He, Feng Gao, Yixue Li","doi":"10.1093/gpbjnl/qzaf011","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf011","url":null,"abstract":"The rapid development of biological and medical examination methods has vastly expanded personal biomedical information, including molecular, cellular, image, and electronic health record datasets. Integrating this wealth of information enables precise disease diagnosis, biomarker identification, and treatment design in clinical settings. Artificial intelligence (AI) techniques, particularly deep learning models, have been extensively employed in biomedical applications, demonstrating increased precision, efficiency, and generalization. The success of the large language and vision models further significantly extends their biomedical applications. However, challenges remain in learning these multimodal biomedical datasets, such as data privacy, fusion, and model interpretation. In this review, we provided a comprehensive overview of various biomedical data modalities, multi-modal representation learning methods, and the applications of AI in biomedical data integrative analysis. Additionally, we discussed the challenges in applying these deep learning methods and how to better integrate them into biomedical scenarios. We then proposed future directions for adapting deep learning methods with model pre-training and knowledge integration to advance biomedical research and benefit their clinical applications.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluative Methodology for HRD Testing: Development of Standard Tools for Consistency Assessment. HRD测试的评估方法：一致性评估标准工具的开发。

Genomics, proteomics & bioinformatics Pub Date : 2025-02-27 DOI: 10.1093/gpbjnl/qzaf017

Zheng Jia, Yaqing Liu, Shoufang Qu, Wenbin Li, Lin Gao, Lin Dong, Yun Xing, Yadi Cheng, Huan Fang, Yuting Yi, Yuxing Chu, Chao Zhang, Yanming Xie, Chunli Wang, Zhe Li, Zhihong Zhang, Zhipeng Xu, Yang Wang, Wenxin Zhang, Xiaoping Gu, Shuang Yang, Jinghua Li, Liangshen Wei, Yuanting Zheng, Guohui Ding, Leming Shi, Xin Yi, Jianming Ying, Jie Huang

{"title":"Evaluative Methodology for HRD Testing: Development of Standard Tools for Consistency Assessment.","authors":"Zheng Jia, Yaqing Liu, Shoufang Qu, Wenbin Li, Lin Gao, Lin Dong, Yun Xing, Yadi Cheng, Huan Fang, Yuting Yi, Yuxing Chu, Chao Zhang, Yanming Xie, Chunli Wang, Zhe Li, Zhihong Zhang, Zhipeng Xu, Yang Wang, Wenxin Zhang, Xiaoping Gu, Shuang Yang, Jinghua Li, Liangshen Wei, Yuanting Zheng, Guohui Ding, Leming Shi, Xin Yi, Jianming Ying, Jie Huang","doi":"10.1093/gpbjnl/qzaf017","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf017","url":null,"abstract":"Homologous recombination deficiency (HRD) has emerged as a critical prognostic and predictive biomarker in oncology. However, current testing methods, especially those reliant on targeted panels, are plagued by inconsistent results from the same samples. This highlights the urgent need for standardized benchmarks to evaluate HRD assay performance. In phases IIa and IIb of the Chinese HRD Harmonization Project, we developed ten pairs of well-characterized DNA reference materials derived from lung, breast, and melanoma cancer cell lines and their matched normal cell lines, each paired with seven cancer-to-normal mass ratios. Reference datasets for allele-specific copy number variations (ASCNVs) and HRD scores were established and validated based on three sequencing methods and nine analytical pipelines. The Genomic Instability Scores (GIS) of the reference materials ranged from 11 to 96, enabling validation across various thresholds. The ASCNV reference datasets covered a genomic span of 2340 to 2749 Mb, equivalent to 81.2% to 95.4% of the autosomes in the 37d5 reference genome. These benchmarks were subsequently utilized to assess the accuracy and reproducibility of four HRD panel assays, revealing significant variability in both ASCNV detection and HRD scores. The concordance between panel-detected GIS and reference GIS ranged from 0.81 to 0.94, and only two assays exhibited high overall agreement with Myriad MyChoice CDx for HRD classification. This study also identified specific challenges in ASCNV detection in HRD-related regions and the profound impact of high ploidy on consistency. The established HRD reference materials and datasets provide a robust toolkit for objective evaluation of HRD testing.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MS-based Solutions for Single Cell Proteomics. 基于 MS 的单细胞蛋白质组学解决方案。

Genomics, proteomics & bioinformatics Pub Date : 2025-02-22 DOI: 10.1093/gpbjnl/qzaf012

Siqi Li, Shuwei Li, Siqi Liu, Yan Ren

引用次数: 0

The Updated Genome Warehouse: Enhancing Data Value, Security, and Usability to Address Data Expansion. 更新的基因组仓库：增强数据价值、安全性和可用性以应对数据扩展。

Genomics, proteomics & bioinformatics Pub Date : 2025-02-20 DOI: 10.1093/gpbjnl/qzaf010

Yingke Ma, Xuetong Zhao, Yaokai Jia, Zhenxian Han, Caixia Yu, Zhuojing Fan, Zhang Zhang, Jingfa Xiao, Wenming Zhao, Yiming Bao, Meili Chen

{"title":"The Updated Genome Warehouse: Enhancing Data Value, Security, and Usability to Address Data Expansion.","authors":"Yingke Ma, Xuetong Zhao, Yaokai Jia, Zhenxian Han, Caixia Yu, Zhuojing Fan, Zhang Zhang, Jingfa Xiao, Wenming Zhao, Yiming Bao, Meili Chen","doi":"10.1093/gpbjnl/qzaf010","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf010","url":null,"abstract":"The Genome Warehouse (GWH), accessible at https://ngdc.cncb.ac.cn/gwh, is an extensively utilized public repository dedicated to the deposition, management and sharing of genome assembly sequences, annotations, and metadata. This paper highlights noteworthy enhancements to the GWH since the 2021 version, emphasizing substantial advancements in web interfaces for data submission, database functionality updates, and resource integration. Key updates include the reannotation of released prokaryotic genomes, mirroring of genome resources from National Center for Biotechnology Information (NCBI) GenBank and Reference Sequence Database (RefSeq), integration of Poxviridae sequences, implementation of an online batch submission system, enhancements to the quality control system, advanced search capabilities, and the introduction of a controlled-access mechanism for human genome data. These improvements collectively augment the ease and security of data submission and access as well as genome data value, thereby fostering heightened convenience and utility for researchers in the genomics field.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0