bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aquila: a spatial omics database and analysis platform
Authors: Zheng Yimin , Chen Yitian , Ding Xianting , Wong Koon Ho , Cheung Edwin 
Published: October 2022

Abstract
Spatial omics is a rapidly evolving approach for exploring tissue microenvironment and cellular networks by integrating spatial knowledge with transcript or protein expression information. However, there is a lack of databases for users to access and analyze spatial omics data. To address this limitation, we developed Aquila, a comprehensive platform for managing and analyzing spatial omics data. Aquila contains 107 datasets from 30 diseases, including 6500+ regions of interest, and 15.7 million cells. The database covers studies from spatial transcriptome and proteome analyses, 2D and 3D experiments, and different technologies. Aquila provides visualization of spatial omics data in multiple formats such as spatial cell distribution, spatial expression and co-localization of markers. Aquila also lets users perform many basic and advanced spatial analyses on any dataset. In addition, users can submit their own spatial omics data for visualization and analysis in a safe and secure environment. Finally, Aquila can be installed as an individual app on a desktop and offers the RESTful API service for power users to access the database. Overall, Aquila provides a detailed insight into transcript and protein expression in tissues from a spatial perspective. Aquila is available at https://aquila.cheunglab.org.
PAT: a comprehensive database of prokaryotic antimicrobial toxins
Authors: Liu Ya , Liu Sheng , Pan Zhuo , Ren Yu , Jiang Yiru , Wang Feng , Li Dan-dan , Li Yue-zhong , Zhang Zheng 
Published: October 2022

Abstract
Antimicrobial toxins help prokaryotes win competitive advantages in intraspecific or interspecific conflicts and are also a critical factor affecting the pathogenicity of many pathogens that threaten human health. Although many studies have revealed that antagonism based on antimicrobial toxins plays a central role in prokaryotic life, a database on antimicrobial toxins remains lacking. Here, we present the prokaryotic antimicrobial toxin database (PAT, http://bioinfo.qd.sdu.edu.cn/PAT/), a comprehensive data resource collection on experimentally validated antimicrobial toxins. PAT has organized information, derived from the reported literature, on antimicrobial toxins, as well as the corresponding immunity proteins, delivery mechanisms, toxin activities, structural characteristics, sequences, etc. Moreover, we also predict potential antimicrobial toxins in prokaryotic reference genomes and show the taxonomic information and environmental distribution of typical antimicrobial toxins. These details have been fully incorporated into the PAT database, where users can browse, search, download, analyse and view informative statistics and detailed information. PAT resources have already been used in our prediction and identification of prokaryotic antimicrobial toxins and may contribute to promoting the efficient investigation of antimicrobial toxin functions, the discovery of novel antimicrobial toxins, and an improved understanding of the biological roles and significance of these toxins.
Molecular basis of dual anti-CRISPR and auto-regulatory functions of AcrIF24
Authors: Kim Gi Eob , Lee So Yeon , Birkholz Nils , Kamata Kotaro , Jeong Jae-Hee , Kim Yeon-Gil , Fineran Peter C , Park Hyun Ho 
Published: October 2022

Abstract
CRISPR-Cas systems are adaptive immune systems in bacteria and archaea that provide resistance against phages and other mobile genetic elements. To fight against CRISPR-Cas systems, phages and archaeal viruses encode anti-CRISPR (Acr) proteins that inhibit CRISPR-Cas systems. The expression of acr genes is controlled by anti-CRISPR-associated (Aca) proteins encoded within acr-aca operons. AcrIF24 is a recently identified Acr that inhibits the type I-F CRISPR-Cas system. Interestingly, AcrIF24 was predicted to be a dual-function Acr and Aca. Here, we elucidated the crystal structure of AcrIF24 from Pseudomonas aeruginosa and identified its operator sequence within the regulated acr-aca operon promoter. The structure of AcrIF24 has a novel domain composition, with wing, head and body domains. The body domain is responsible for recognition of promoter DNA for Aca regulatory activity. We also revealed that AcrIF24 directly bound to type I-F Cascade, specifically to Cas7 via its head domain as part of its Acr mechanism. Our results provide new molecular insights into the mechanism of a dual functional Acr-Aca protein.
Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers
Authors: Tao Yifeng , Ma Xiaojun , Palmer Drake , Schwartz Russell , Lu Xinghua , Osmanbeyoglu Hatice Ulku 
Published: October 2022

AbstractCancer is a disease of gene dysregulation, where cells acquire somatic and epigenetic alterations that drive aberrant cellular signaling. These alterations adversely impact transcriptional programs and cause profound changes in gene expression. Interpreting somatic alterations within context-specific transcriptional programs will facilitate personalized therapeutic decisions but is a monumental task. Toward this goal, we develop a partially interpretable neural network model called Chromatin-informed Inference of Transcriptional Regulators Using Self-attention mechanism (CITRUS). CITRUS models the impact of somatic alterations on transcription factors and downstream transcriptional programs. Our approach employs a self-attention mechanism to model the contextual impact of somatic alterations. Furthermore, CITRUS uses a layer of hidden nodes to explicitly represent the state of transcription factors (TFs) to learn the relationships between TFs and their target genes based on TF binding motifs in the open chromatin regions of tumor samples. We apply CITRUS to genomic, transcriptomic, and epigenomic data from 17 cancer types profiled by The Cancer Genome Atlas. CITRUS predicts patient-specific TF activities and reveals transcriptional program variations between and within tumor types. We show that CITRUS yields biological insights into delineating TFs associated with somatic alterations in individual tumors. Thus, CITRUS is a promising tool for precision oncology.
AmyloGraph: a comprehensive database of amyloid–amyloid interactions
Authors: Burdukiewicz Michał , Rafacz Dominik , Barbach Agnieszka , Hubicka Katarzyna , Bąkała Laura , Lassota Anna , Stecko Jakub , Szymańska Natalia , Wojciechowski Jakub W , Kozakiewicz Dominika , Szulc Natalia , Chilimoniuk Jarosław , Jęśkowiak Izabela , Gąsior-Głogowska Marlena , Kotulska Małgorzata 
Published: October 2022

Abstract
Information about the impact of interactions between amyloid proteins on their fibrillization propensity is scattered among many experimental articles and presented in unstructured form. We manually curated information located in almost 200 publications (selected out of 562 initially considered), obtaining details of 883 experimentally studied interactions between 46 amyloid proteins or peptides. We also proposed a novel standardized terminology for the description of amyloid–amyloid interactions, which is included in our database, covering all currently known types of such a cross-talk, including inhibition of fibrillization, cross-seeding and other phenomena. The new approach allows for more specific studies on amyloids and their interactions, by providing very well-defined data. AmyloGraph, an online database presenting information on amyloid–amyloid interactions, is available at (http://AmyloGraph.com/). Its functionalities are also accessible as the R package (https://github.com/KotulskaLab/AmyloGraph). AmyloGraph is the only publicly available repository for experimentally determined amyloid–amyloid interactions.
SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update
Authors: Lo Surdo Prisca , Iannuccelli Marta , Contino Silvia , Castagnoli Luisa , Licata Luana , Cesareni Gianni , Perfetto Livia 
Published: October 2022

Abstract
The SIGnaling Network Open Resource (SIGNOR 3.0, https://signor.uniroma2.it) is a public repository that captures causal information and represents it according to an ‘activity-flow’ model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction.
isomiRdb: microRNA expression at isoform resolution
Authors: Aparicio-Puerta Ernesto , Hirsch Pascal , Schmartz Georges P , Fehlmann Tobias , Keller Verena , Engel Annika , Kern Fabian , Hackenberg Michael , Keller Andreas 
Published: October 2022

Abstract
A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients’ samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (&gt;1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.
Integrated multi-omics approach revealed cellular senescence landscape
Authors: Song Qiao , Hou Yuli , Zhang Yiyin , Liu Jing , Wang Yaqi , Fu Jingxuan , Zhang Chi , Cao Min , Cui Yuting , Zhang Xiaomin , Wang Xiaoling , Zhang Jingjing , Liu Congcong , Zhang Yingzhen , Wang Peichang 
Published: October 2022

AbstractCellular senescence is a complex multifactorial biological phenomenon that plays essential roles in aging, and aging-related diseases. During this process, the senescent cells undergo gene expression altering and chromatin structure remodeling. However, studies on the epigenetic landscape of senescence using integrated multi-omics approaches are limited. In this research, we performed ATAC-seq, RNA-seq and ChIP-seq on different senescent types to reveal the landscape of senescence and identify the prime regulatory elements. We also obtained 34 key genes and deduced that NAT1, PBX1 and RRM2, which interacted with each other, could be the potential markers of aging and aging-related diseases. In summary, our work provides the landscape to study accessibility dynamics and transcriptional regulations in cellular senescence. The application of this technique in different types of senescence allows us to identify the regulatory elements responsible for the substantial regulation of transcription, providing the insights into molecular mechanisms of senescence.
CRISPR/Cas9-induced structural variations expand in T lymphocytes in vivo
Authors: Wu Jinchun , Zou Ziye , Liu Yang , Liu Xuhao , Zhangding Zhengrong , Xu Mo , Hu Jiazhi 
Published: October 2022

Abstract
CRISPR/Cas9 has been adapted to disrupt endogenous genes in adoptive T-lymphocyte therapy to prevent graft-versus-host disease. However, genome editing also generates prevalent deleterious structural variations (SVs), including chromosomal translocations and large deletions, raising safety concerns about reinfused T cells. Here, we dynamically monitored the progression of SVs in a mouse model of T-cell receptor (TCR)-transgenic T-cell adoptive transfer, mimicking TCR T therapeutics. Remarkably, CRISPR/Cas9-induced SVs persist and undergo clonal expansion in vivo after three weeks or even two months, evidenced by high enrichment and low junctional diversity of identified SVs post infusion. Specifically, we detected 128 expanded translocations, with 20 615 as the highest number of amplicons. The identified SVs are stochastically selected among different individuals and show an inconspicuous locus preference. Similar to SVs, viral DNA integrations are routinely detected in edited T cells and also undergo clonal expansion. The persistent SVs and viral DNA integrations in the infused T cells may constantly threaten genome integrity, drawing immediate attention to the safety of CRISPR/Cas9-engineered T cells mediated immunotherapy.
Genenames.org: the HGNC resources in 2023
Authors: Seal Ruth L , Braschi Bryony , Gray Kristian , Jones Tamsin E M , Tweedie Susan , Haim-Vilmovsky Liora , Bruford Elspeth A 
Published: October 2022

Abstract
The HUGO Gene Nomenclature Committee (HGNC) assigns unique symbols and names to human genes. The HGNC database (www.genenames.org) currently contains over 43 000 approved gene symbols, over 19 200 of which are assigned to protein-coding genes, 14 000 to pseudogenes and nearly 9000 to non-coding RNA genes. The public website, www.genenames.org, displays all approved nomenclature within Symbol Reports that contain data curated by HGNC nomenclature advisors and links to related genomic, clinical, and proteomic information. Here, we describe updates to our resource, including improvements to our search facility and new download features.
SPASCER: spatial transcriptomics annotation at single-cell resolution
Authors: Fan Zhiwei , Luo Yangyang , Lu Huifen , Wang Tiangang , Feng YuZhou , Zhao Weiling , Kim Pora , Zhou Xiaobo 
Published: October 2022

Abstract
In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and provides novel insights into diverse spatially related biological contexts. Even though two spatial transcriptomics databases exist, they provide limited analytical information. Information such as spatial heterogeneity of genes and cells, cell-cell communication activities in space, and the cell type compositions in the microenvironment are critical clues to unveil the mechanism of tumorigenesis and embryo differentiation. Therefore, we constructed a new spatial transcriptomics database, named SPASCER (https://ccsm.uth.edu/SPASCER), designed to help understand the heterogeneity of tissue organizations, region-specific microenvironment, and intercellular interactions across tissue architectures at multiple levels. SPASCER contains datasets from 43 studies, including 1082 sub-datasets from 16 organ types across four species. scRNA-seq was integrated to deconvolve/map spatial transcriptomics, and processed with spatial cell-cell interaction, gene pattern and pathway enrichment analysis. Cell–cell interactions and gene regulation network of scRNA-seq from matched spatial transcriptomics were performed as well. The application of SPASCER will provide new insights into tissue architecture and a solid foundation for the mechanistic understanding of many biological processes in healthy and diseased tissues.
KRCC1, a modulator of the DNA damage response
Authors: Neizer-Ashun Fiifi , Dwivedi Shailendra Kumar Dhar , Dey Anindya , Thavathiru Elangovan , Berry William L , Lees-Miller Susan Patricia , Mukherjee Priyabrata , Bhattacharya Resham 
Published: October 2022

Abstract
The lysine-rich coiled-coil 1 (KRCC1) protein is overexpressed in multiple malignancies, including ovarian cancer, and overexpression correlates with poor overall survival. Despite a potential role in cancer progression, the biology of KRCC1 remains elusive. Here, we characterize the biology of KRCC1 and define its role in the DNA damage response and in cell cycle progression. We demonstrate that KRCC1 associates with the checkpoint kinase 1 (CHK1) upon DNA damage and regulates the CHK1-mediated checkpoint. KRCC1 facilitates RAD51 recombinase foci formation and augments homologous recombination repair. Furthermore, KRCC1 is required for proper S-phase progression and subsequent mitotic entry. Our findings uncover a novel component of the DNA damage response and a potential link between cell cycle, associated damage response and DNA repair.
CellTracer: a comprehensive database to dissect the causative multilevel interplay contributing to cell development trajectories
Authors: Guo Qiuyan , Wang Peng , Liu Qian , Hao Yangyang , Gao Yue , Qi Yue , Xu Rongji , Chen Hongyan , Xin Mengyu , Wu Xiaoting , Sun Rui , Zhi Hui , Zhang Yunpeng , Ning Shangwei , Li Xia 
Published: October 2022

Abstract
During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.
ChromLoops: a comprehensive database for specific protein-mediated chromatin loops in diverse organisms
Authors: Zhou Qiangwei , Cheng Sheng , Zheng Shanshan , Wang Zhenji , Guan Pengpeng , Zhu Zhixian , Huang Xingyu , Zhou Cong , Li Guoliang 
Published: October 2022

Abstract
Chromatin loops (or chromatin interactions) are important elements of chromatin structures. Disruption of chromatin loops is associated with many diseases, such as cancer and polydactyly. A few methods, including ChIA-PET, HiChIP and PLAC-Seq, have been proposed to detect high-resolution, specific protein-mediated chromatin loops. With rapid progress in 3D genomic research, ChIA-PET, HiChIP and PLAC-Seq datasets continue to accumulate, and effective collection and processing for these datasets are urgently needed. Here, we developed a comprehensive, multispecies and specific protein-mediated chromatin loop database (ChromLoops, https://3dgenomics.hzau.edu.cn/chromloops), which integrated 1030 ChIA-PET, HiChIP and PLAC-Seq datasets from 13 species, and documented 1 491 416 813 high-quality chromatin loops. We annotated genes and regions overlapping with chromatin loop anchors with rich functional annotations, such as regulatory elements (enhancers, super-enhancers and silencers), variations (common SNPs, somatic SNPs and eQTLs), and transcription factor binding sites. Moreover, we identified genes with high-frequency chromatin interactions in the collected species. In particular, we identified genes with high-frequency interactions in cancer samples. We hope that ChromLoops will provide a new platform for studying chromatin interaction regulation in relation to biological processes and disease.
Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits
Authors: Pan Siyu , Kang Hongen , Liu Xinxuan , Lin Shiqi , Yuan Na , Zhang Zhang , Bao Yiming , Jia Peilin 
Published: October 2022

Abstract
A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.