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  • Oxford University Press (OUP)  (12)
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  • Oxford University Press (OUP)  (12)
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  • 1
    Online Resource
    Online Resource
    The Chrysanthemum lavandulifolium genome and the molecular mechanism underlying diverse capitulum types
    Oxford University Press (OUP) ; 2022
    In:  Horticulture Research Vol. 9 ( 2022-01-05)
    Details
    In: Horticulture Research, Oxford University Press (OUP), Vol. 9 ( 2022-01-05)
    Abstract: Cultivated chrysanthemum (Chrysanthemum × morifolium Ramat.) is a beloved ornamental crop due to the diverse capitula types among varieties, but the molecular mechanism of capitulum development remains unclear. Here, we report a 2.60 Gb chromosome-scale reference genome of C. lavandulifolium, a wild Chrysanthemum species found in China, Korea and Japan. The evolutionary analysis of the genome revealed that only recent tandem duplications occurred in the C. lavandulifolium genome after the shared whole genome triplication (WGT) in Asteraceae. Based on the transcriptomic profiling of six important developmental stages of the radiate capitulum in C. lavandulifolium, we found genes in the MADS-box, TCP, NAC and LOB gene families that were involved in disc and ray floret primordia differentiation. Notably, NAM and LOB30 homologs were specifically expressed in the radiate capitulum, suggesting their pivotal roles in the genetic network of disc and ray floret primordia differentiation in chrysanthemum. The present study not only provides a high-quality reference genome of chrysanthemum but also provides insight into the molecular mechanism underlying the diverse capitulum types in chrysanthemum.
    Type of Medium: Online Resource
    ISSN: 2052-7276
    URL: Article
    DOI: 10.1093/hr/uhab022
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2781828-7
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  • 2
    Online Resource
    Online Resource
    Combined Detection of NUDT15 Variants Could Highly Predict Thiopurine-induced Leukopenia in Chinese Patients with Inflammatory Bowel Disease : A Multicenter Analysis
    Oxford University Press (OUP) ; 2017
    In:  Inflammatory Bowel Diseases Vol. 23, No. 9 ( 2017-09), p. 1592-1599
    Details
    In: Inflammatory Bowel Diseases, Oxford University Press (OUP), Vol. 23, No. 9 ( 2017-09), p. 1592-1599
    Type of Medium: Online Resource
    ISSN: 1078-0998
    URL: Article
    DOI: 10.1097/MIB.0000000000001148
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2017
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  • 3
    Online Resource
    Online Resource
    Computational principles and practice for decoding immune contexture in the tumor microenvironment
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 3 ( 2021-05-20)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 3 ( 2021-05-20)
    Abstract: Tumor-infiltrating immune cells (TIICs) have been recognized as crucial components of the tumor microenvironment (TME) and induced both beneficial and adverse consequences for tumorigenesis as well as outcome and therapy (particularly immunotherapy). Computer-aided investigation of immune cell components in the TME has become a promising avenue to better understand the interplay between the immune system and tumors. In this study, we presented an overview of data sources, computational methods and software tools, as well as their application in inferring the composition of tumor-infiltrating immune cells in the TME. In parallel, we explored the future perspectives and challenges that may be faced with more accurate quantitative infiltration of immune cells in the future. Together, our study provides a little guide for scientists in the field of clinical and experimental immunology to look for dedicated resources and more competent tools for accelerating the unraveling of tumor-immune interactions with the implication in precision immunotherapy.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa075
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Deep learning-based advances and applications for single-cell RNA-sequencing data analysis
    Oxford University Press (OUP) ; 2022
    In:  Briefings in Bioinformatics Vol. 23, No. 1 ( 2022-01-17)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 23, No. 1 ( 2022-01-17)
    Abstract: The rapid development of single-cell RNA-sequencing (scRNA-seq) technology has raised significant computational and analytical challenges. The application of deep learning to scRNA-seq data analysis is rapidly evolving and can overcome the unique challenges in upstream (quality control and normalization) and downstream (cell-, gene- and pathway-level) analysis of scRNA-seq data. In the present study, recent advances and applications of deep learning-based methods, together with specific tools for scRNA-seq data analysis, were summarized. Moreover, the future perspectives and challenges of deep-learning techniques regarding the appropriate analysis and interpretation of scRNA-seq data were investigated. The present study aimed to provide evidence supporting the biomedical application of deep learning-based tools and may aid biologists and bioinformaticians in navigating this exciting and fast-moving area.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbab473
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    Multiomics integration-based molecular characterizations of COVID-19
    Oxford University Press (OUP) ; 2022
    In:  Briefings in Bioinformatics Vol. 23, No. 1 ( 2022-01-17)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 23, No. 1 ( 2022-01-17)
    Abstract: The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbab485
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Transcription factors RhbZIP17 and RhWRKY30 enhance resistance to Botrytis cinerea by increasing lignin content in rose petals
    Oxford University Press (OUP) ; 2024
    In:  Journal of Experimental Botany ( 2024-01-05)
    Details
    In: Journal of Experimental Botany, Oxford University Press (OUP), ( 2024-01-05)
    Abstract: The petals of ornamental plants such as roses (Rosa sp.) are the most economically important organs. This delicate, short-lived plant tissue is highly susceptible to pathogens, in large part because the walls of petal cells are typically thinner and more flexible compared to leaf cells, allowing the petals to fold and bend without breaking. The cell wall is a dynamic structure that rapidly alters its composition in response to pathogen infection, thereby reinforcing its stability and boosting plant resistance against diseases. However, little is known about how dynamic changes in the cell wall contribute to resistance to Botrytis cinerea in rose petals. Here, we show that the B. cinerea–induced transcription factor RhbZIP17 is required for the defense response of rose. RhbZIP17 is associated with phenylpropanoid biosynthesis and binds to the promoter of the lignin biosynthesis gene RhCAD1, activating its expression. Lignin content showed a significant increase under gray mold infection compared to the control. RhCAD1 functions in the metabolic regulation of lignin production and, consequently, disease resistance, as revealed by transient silencing and overexpression in rose petals. The WRKY transcription factor RhWRKY30 is also required to activate RhCAD1 expression and enhance resistance against B. cinerea. We propose that RhbZIP17 and RhWRKY30 increase lignin biosynthesis, improve the resistance of rose petals to B. cinerea, and regulate RhCAD1 expression.
    Type of Medium: Online Resource
    ISSN: 0022-0957 , 1460-2431
    URL: Article
    DOI: 10.1093/jxb/erad473
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
    detail.hit.zdb_id: 1466717-4
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 3 ( 2021-05-20)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 3 ( 2021-05-20)
    Abstract: Long noncoding RNAs (lncRNAs) have been associated with cancer immunity regulation and the tumor microenvironment (TME). However, functions of lncRNAs of tumor-infiltrating B lymphocytes (TIL-Bs) and their clinical significance have not yet been fully elucidated. In the present study, a machine learning-based computational framework is presented for the identification of lncRNA signature of TIL-Bs (named ‘TILBlncSig’) through integrative analysis of immune, lncRNA and clinical profiles. The TILBlncSig comprising eight lncRNAs (TNRC6C-AS1, WASIR2, GUSBP11, OGFRP1, AC090515.2, PART1, MAFG-DT and LINC01184) was identified from the list of 141 B-cell-specific lncRNAs. The TILBlncSig was capable of distinguishing worse compared with improved survival outcomes across different independent patient datasets and was also independent of other clinical covariates. Functional characterization of TILBlncSig revealed it to be an indicator of infiltration of mononuclear immune cells (i.e. natural killer cells, B-cells and mast cells), and it was associated with hallmarks of cancer, as well as immunosuppressive phenotype. Furthermore, the TILBlncSig revealed predictive value for the survival outcome and immunotherapy response of patients with anti-programmed death-1 (PD-1) therapy and added significant predictive power to current immune checkpoint gene markers. The present study has highlighted the value of the TILBlncSig as an indicator of immune cell infiltration in the TME from a noncoding RNA perspective and strengthened the potential application of lncRNAs as predictive biomarkers of immunotherapy response, which warrants further investigation.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa047
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 8
    Online Resource
    Online Resource
    Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer
    Oxford University Press (OUP) ; 2020
    In:  Briefings in Bioinformatics Vol. 21, No. 5 ( 2020-09-25), p. 1742-1755
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 21, No. 5 ( 2020-09-25), p. 1742-1755
    Abstract: Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbz118
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 9
    Online Resource
    Online Resource
    Mechanistically derived patient-level framework for precision medicine identifies a personalized immune prognostic signature in high-grade serous ovarian cancer
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 3 ( 2021-05-20)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 3 ( 2021-05-20)
    Abstract: An accurate prognosis assessment for cancer patients could aid in guiding clinical decision-making. Reliance on traditional clinical features alone in a complex clinical environment is challenging and unsatisfactory in the era of precision medicine; thus, reliable prognostic biomarkers are urgently required to improve a patient staging system. In this study, we proposed a patient-level computational framework from mechanistic and translational perspectives to establish a personalized prognostic signature (named PLPPS) in high-grade serous ovarian carcinoma (HGSOC). The PLPPS composed of 68 immune genes achieved accurate prognostic risk stratification for 1190 patients in the meta-training cohort and was rigorously validated in multiple cross-platform independent cohorts comprising 792 HGSOC patients. Furthermore, the PLPPS was shown to be the better prognostic factor compared with clinical parameters in the univariate analysis and retained a significant independent association with prognosis after adjusting for clinical parameters in the multivariate analysis. In benchmark comparisons, the performance of PLPPS (hazard ratio (HR), 1.371; concordance index (C-index), 0.604 and area under the curve (AUC), 0.637) is comparable to or better than other published gene signatures (HR, 0.972 to 1.340; C-index, 0.495 to 0.592 and AUC, 0.48–0.624). With further validation in prospective clinical trials, we hope that the PLPPS might become a promising genomic tool to guide personalized management and decision-making of HGSOC in clinical practice.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa069
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 10
    Online Resource
    Online Resource
    Toxicity and prosocial behaviors in massively multiplayer online games: The role of mutual dependence, power, and passion
    Oxford University Press (OUP) ; 2022
    In:  Journal of Computer-Mediated Communication Vol. 27, No. 6 ( 2022-09-15)
    Details
    In: Journal of Computer-Mediated Communication, Oxford University Press (OUP), Vol. 27, No. 6 ( 2022-09-15)
    Abstract: Understanding factors that predict toxic and prosocial behavior in massively multiplayer online (MMO) games has drawn a great deal of scholarly attention. Prior work on this topic has primarily focused on individual and technological factors while overlooking the role of interpersonal dynamics. To fill this gap, this study examines if and how players’ perceptions of mutual dependence and power in MMO games are related to toxicity and prosocial behavior in games. Results from a survey of 782 Chinese game players suggest that players’ perceived power is positively related to prosocial behavior in games. Perceived mutual dependence and power are also indirectly related to prosocial and toxic behaviors through players’ passion for games. This study has theoretical implications for scholarship on toxicity, prosocial behaviors, and gameplay, while also providing design and policy implications for MMO games.
    Type of Medium: Online Resource
    ISSN: 1083-6101
    URL: Article
    DOI: 10.1093/jcmc/zmac017
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2024777-1
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