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  • Oxford University Press (OUP)  (755)
  • 1
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022
    Oxford University Press (OUP) ; 2022
    In:  Nucleic Acids Research Vol. 50, No. D1 ( 2022-01-07), p. D27-D38
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 50, No. D1 ( 2022-01-07), p. D27-D38
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkab951
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 2
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023
    Oxford University Press (OUP) ; 2023
    In:  Nucleic Acids Research Vol. 51, No. D1 ( 2023-01-06), p. D18-D28
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 51, No. D1 ( 2023-01-06), p. D18-D28
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global academic and industrial communities. With the explosive accumulation of multi-omics data generated at an unprecedented rate, CNCB-NGDC constantly expands and updates core database resources by big data archive, integrative analysis and value-added curation. In the past year, efforts have been devoted to integrating multiple omics data, synthesizing the growing knowledge, developing new resources and upgrading a set of major resources. Particularly, several database resources are newly developed for infectious diseases and microbiology (MPoxVR, KGCoV, ProPan), cancer-trait association (ASCancer Atlas, TWAS Atlas, Brain Catalog, CCAS) as well as tropical plants (TCOD). Importantly, given the global health threat caused by monkeypox virus and SARS-CoV-2, CNCB-NGDC has newly constructed the monkeypox virus resource, along with frequent updates of SARS-CoV-2 genome sequences, variants as well as haplotypes. All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkac1073
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 3
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021
    Oxford University Press (OUP) ; 2021
    In:  Nucleic Acids Research Vol. 49, No. D1 ( 2021-01-08), p. D18-D28
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 49, No. D1 ( 2021-01-08), p. D18-D28
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multi-omics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkaa1022
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 4
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    Database Resources of the National Genomics Data Center in 2020
    Oxford University Press (OUP) ; 2019
    In:  Nucleic Acids Research ( 2019-11-08)
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), ( 2019-11-08)
    Abstract: The National Genomics Data Center (NGDC) provides a suite of database resources to support worldwide research activities in both academia and industry. With the rapid advancements in higher-throughput and lower-cost sequencing technologies and accordingly the huge volume of multi-omics data generated at exponential scales and rates, NGDC is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. In the past year, efforts for update have been mainly devoted to BioProject, BioSample, GSA, GWH, GVM, NONCODE, LncBook, EWAS Atlas and IC4R. Newly released resources include three human genome databases (PGG.SNV, PGG.Han and CGVD), eLMSG, EWAS Data Hub, GWAS Atlas, iSheep and PADS Arsenal. In addition, four web services, namely, eGPS Cloud, BIG Search, BIG Submission and BIG SSO, have been significantly improved and enhanced. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkz913
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 5
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    Large expert-curated database for benchmarking document similarity detection in biomedical literature search
    Oxford University Press (OUP) ; 2019
    In:  Database Vol. 2019 ( 2019-01-01)
    Details
    In: Database, Oxford University Press (OUP), Vol. 2019 ( 2019-01-01)
    Abstract: Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.
    Type of Medium: Online Resource
    ISSN: 1758-0463
    URL: Article
    DOI: 10.1093/database/baz085
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2496706-3
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  • 6
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    Prospective observational cohort study on grading the severity of postoperative complications in global surgery research
    Oxford University Press (OUP) ; 2019
    In:  British Journal of Surgery Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Details
    In: British Journal of Surgery, Oxford University Press (OUP), Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Abstract: The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally.
    Type of Medium: Online Resource
    ISSN: 0007-1323 , 1365-2168
    URL: Article
    DOI: 10.1002/bjs.11025
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2006309-X
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  • 7
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    The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder
    Oxford University Press (OUP) ; 2022
    In:  Psychoradiology Vol. 2, No. 1 ( 2022-06-09), p. 32-42
    Details
    In: Psychoradiology, Oxford University Press (OUP), Vol. 2, No. 1 ( 2022-06-09), p. 32-42
    Abstract: Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.
    Type of Medium: Online Resource
    ISSN: 2634-4416
    URL: Article
    DOI: 10.1093/psyrad/kkac005
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 3076092-6
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  • 8
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    Corrigendum to: The TianQin project: current progress on science and technology
    Oxford University Press (OUP) ; 2021
    In:  Progress of Theoretical and Experimental Physics Vol. 2021, No. 5 ( 2021-05-18)
    Details
    In: Progress of Theoretical and Experimental Physics, Oxford University Press (OUP), Vol. 2021, No. 5 ( 2021-05-18)
    Type of Medium: Online Resource
    ISSN: 2050-3911
    URL: Article
    DOI: 10.1093/ptep/ptaa165
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2705045-2
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  • 9
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    The TianQin project: Current progress on science and technology
    Oxford University Press (OUP) ; 2021
    In:  Progress of Theoretical and Experimental Physics Vol. 2021, No. 5 ( 2021-05-18)
    Details
    In: Progress of Theoretical and Experimental Physics, Oxford University Press (OUP), Vol. 2021, No. 5 ( 2021-05-18)
    Abstract: TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 \, {\rm km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} \, {\rm Hz}$ and $1 \, {\rm Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 \, {\rm cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 \, {\rm m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019—the first-round result shows that the satellite has exceeded all of its mission requirements.
    Type of Medium: Online Resource
    ISSN: 2050-3911
    URL: Article
    DOI: 10.1093/ptep/ptaa114
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2705045-2
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  • 10
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    DPHL: A DIA Pan-Human Protein Mass Spectrometry Library for Robust Biomarker Discovery
    Oxford University Press (OUP) ; 2020
    In:  Genomics, Proteomics & Bioinformatics Vol. 18, No. 2 ( 2020-04-01), p. 104-119
    Details
    In: Genomics, Proteomics & Bioinformatics, Oxford University Press (OUP), Vol. 18, No. 2 ( 2020-04-01), p. 104-119
    Abstract: To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.
    Type of Medium: Online Resource
    ISSN: 1672-0229 , 2210-3244
    URL: Article
    DOI: 10.1016/j.gpb.2019.11.008
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2233708-8
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