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  1. 1561
    “…Returned ranked gene lists contain genes that were previously published in association with the search terms, as well as genes predicted to be associated with the terms based on data integration from multiple sources. The search results are presented with interactive visualizations. …”
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    Online Artículo Texto
    Geneshot: search engine for ranking genes from arbitrary text queries
  2. 1562
    “…Since then, AI in medicine has gradually evolved toward essentially data-driven approaches with great results in image analysis. However, data integration, storage, and management still present clear challenges among which the lack of explanability of the results produced by data-driven AI methods. …”
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    Online Artículo Texto
    Artificial Intelligence in Health Informatics: Hype or Reality?
  3. 1563
    “…In this cascade, LLP1 forms a key regulatory unit in both within-plant and between-plant propagation of immunity. The data integrate molecular components of SAR into systemic signaling networks that are separate from conventional, SA-associated innate immune mechanisms. …”
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    Systemic acquired resistance networks amplify airborne defense cues
  4. 1564
    “…Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. …”
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    EAGLE—A Scalable Query Processing Engine for Linked Sensor Data †
  5. 1565
    “…This complicates the unit-cell determination, indexing, data integration and scaling of X-ray diffraction data. …”
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    Online Artículo Texto
    Non-merohedral twinning: from minerals to proteins
  6. 1566
    “…Warehousing heterogeneous, dynamic biological data is a key technique for biological data integration as it greatly improves performance. However, it requires complex maintenance procedures to update the warehouse in light of the changes to the sources. …”
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    BioDIFF: An Effective Fast Change Detection Algorithm for Biological Annotations
  7. 1567
    Publicado 2020
    “…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. …”
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    Database Resources of the National Genomics Data Center in 2020
  8. 1568
    “…Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.…”
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    From genome sequencing to the discovery of potential biomarkers in liver disease
  9. 1569
    “…The simultaneous analysis of different regulatory levels of biological phenomena by means of multi-omics data integration has proven an invaluable tool in modern precision medicine, yet many processes ultimately paving the way towards disease manifestation remain elusive and have not been studied in this regard. …”
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    Concomitant DNA methylation and transcriptome signatures define epidermal responses to acute solar UV radiation
  10. 1570
    “…Challenges remain relating to cost, data integration, the redesigning of team-based care, and the improvement of user experience, but information and communication technology-based hypertension management is sure to become pivotal in improving public health.…”
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    The current state and future of internet technology-based hypertension management in Japan
  11. 1571
    por Parsons, Thomas, Duffield, Tyler
    Publicado 2020
    “…The 4 main advances influencing the scientific priorities of a recent NIH Office of Behavioral and Social Sciences Research strategic plan include the following: integration of neuroscience into behavioral and social sciences, transformational advances in measurement science, digital intervention platforms, and large-scale population cohorts and data integration. This paper reviews these opportunities for novel brain-behavior characterizations. …”
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    Paradigm Shift Toward Digital Neuropsychology and High-Dimensional Neuropsychological Assessments: Review
  12. 1572
    “…Using a slowly progressing knockin mouse model, we profile the HD striatal chromatin landscape at two early disease stages. Data integration with cell type-specific striatal enhancer and transcriptomic databases demonstrates acceleration of age-related epigenetic remodelling and transcriptional changes at neuronal- and glial-specific genes from prodromal stage, before the onset of motor deficits. …”
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    Age-related and disease locus-specific mechanisms contribute to early remodelling of chromatin structure in Huntington’s disease mice
  13. 1573
    por Vihinen, Mauno
    Publicado 2020
    “…The VariO annotations are readable both for humans and computer programs for advanced data integration and mining.…”
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    Systematics for types and effects of RNA variations
  14. 1574
    “…To further extend applications of genomics within precision public health research, three key cross-cutting challenges will need to be addressed: developing policies that implement precision public health initiatives at multiple levels, improving data integration and developing more rigorous methodologies, and incorporating initiatives that address health equity. …”
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    Advancing precision public health using human genomics: examples from the field and future research opportunities
  15. 1575
    por Palmer, Rohan H. C., Johnson, Emma C., Won, Hyejung, Polimanti, Renato, Kapoor, Manav, Chitre, Apurva, Bogue, Molly A., Benca‐Bachman, Chelsie E., Parker, Clarissa C., Verma, Anurag, Reynolds, Timothy, Ernst, Jason, Bray, Michael, Kwon, Soo Bin, Lai, Dongbing, Quach, Bryan C., Gaddis, Nathan C., Saba, Laura, Chen, Hao, Hawrylycz, Michael, Zhang, Shan, Zhou, Yuan, Mahaffey, Spencer, Fischer, Christian, Sanchez‐Roige, Sandra, Bandrowski, Anita, Lu, Qing, Shen, Li, Philip, Vivek, Gelernter, Joel, Bierut, Laura J., Hancock, Dana B., Edenberg, Howard J., Johnson, Eric O., Nestler, Eric J., Barr, Peter B., Prins, Pjotr, Smith, Desmond J., Akbarian, Schahram, Thorgeirsson, Thorgeir, Walton, Dave, Baker, Erich, Jacobson, Daniel, Palmer, Abraham A., Miles, Michael, Chesler, Elissa J., Emerson, Jake, Agrawal, Arpana, Martone, Maryann, Williams, Robert W.
    Publicado 2021
    “…Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration—particularly between animal model research communities and human genetics and clinical research teams. …”
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    Integration of evidence across human and model organism studies: A meeting report
  16. 1576
    “…A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. …”
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    Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C
  17. 1577
    “…We highlight the importance of data integration on the identification of drug combinations. …”
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    Machine learning approaches for drug combination therapies
  18. 1578
    por Wendisch, Daniel, Dietrich, Oliver, Mari, Tommaso, von Stillfried, Saskia, Ibarra, Ignacio L., Mittermaier, Mirja, Mache, Christin, Chua, Robert Lorenz, Knoll, Rainer, Timm, Sara, Brumhard, Sophia, Krammer, Tobias, Zauber, Henrik, Hiller, Anna Luisa, Pascual-Reguant, Anna, Mothes, Ronja, Bülow, Roman David, Schulze, Jessica, Leipold, Alexander M., Djudjaj, Sonja, Erhard, Florian, Geffers, Robert, Pott, Fabian, Kazmierski, Julia, Radke, Josefine, Pergantis, Panagiotis, Baßler, Kevin, Conrad, Claudia, Aschenbrenner, Anna C., Sawitzki, Birgit, Landthaler, Markus, Wyler, Emanuel, Horst, David, Hippenstiel, Stefan, Hocke, Andreas, Heppner, Frank L., Uhrig, Alexander, Garcia, Carmen, Machleidt, Felix, Herold, Susanne, Elezkurtaj, Sefer, Thibeault, Charlotte, Witzenrath, Martin, Cochain, Clément, Suttorp, Norbert, Drosten, Christian, Goffinet, Christine, Kurth, Florian, Schultze, Joachim L., Radbruch, Helena, Ochs, Matthias, Eils, Roland, Müller-Redetzky, Holger, Hauser, Anja E., Luecken, Malte D., Theis, Fabian J., Conrad, Christian, Wolff, Thorsten, Boor, Peter, Selbach, Matthias, Saliba, Antoine-Emmanuel, Sander, Leif Erik
    Publicado 2021
    “…Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. …”
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    SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis
  19. 1579
    “…Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. …”
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    How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow
  20. 1580
    “…Finally, we show how FAUST's phenotypes can be used to perform cross-study data integration in the presence of diverse staining panels. …”
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    New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy
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