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  1. AU="Fu, Yuntian"
  2. AU="Spigland, N"
  3. AU="Blum, Jonathan"
  4. AU="Philips, Santosh"
  5. AU="Lin, Xingyu"
  6. AU=Ko C W AU=Ko C W
  7. AU="Yang, Shucai"
  8. AU="Orton, Jane"
  9. AU="Remer, Thomas"
  10. AU="Blanco Álvarez, Adoración"
  11. AU="Nestor Laurier, Engone Obiang"
  12. AU="Huberty, Fanny"
  13. AU="Ju, Beomsoo"
  14. AU="Yu, Jessica"
  15. AU="Yamada, Hiroyuki"
  16. AU="Uruski, Pawel"
  17. AU="Laranjeiro, Ricardo"
  18. AU="Ahmadi, Reza"
  19. AU="Hoet, Peter H.M."
  20. AU=Sengupta Sohini AU=Sengupta Sohini
  21. AU="Conlon, Dara"
  22. AU=Endeman Henrik AU=Endeman Henrik
  23. AU="New, Sophie E.P"

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  1. Artikel ; Online: High-efficiency and reliable same-parent thermoelectric modules using Mg

    Jiang, Meng / Fu, Yuntian / Zhang, Qihao / Hu, Zhongliang / Huang, Aibin / Wang, Shuling / Wang, Lianjun / Jiang, Wan

    National science review

    2023  Band 10, Heft 6, Seite(n) nwad095

    Abstract: Thermoelectric modules can convert waste heat directly into useful electricity, providing a clean and sustainable way to use fossil energy more efficiently. ... ...

    Abstract Thermoelectric modules can convert waste heat directly into useful electricity, providing a clean and sustainable way to use fossil energy more efficiently. Mg
    Sprache Englisch
    Erscheinungsdatum 2023-04-13
    Erscheinungsland China
    Dokumenttyp Journal Article
    ZDB-ID 2745465-4
    ISSN 2053-714X ; 2053-714X
    ISSN (online) 2053-714X
    ISSN 2053-714X
    DOI 10.1093/nsr/nwad095
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Fully inkjet-printed Ag

    Liu, Yan / Zhang, Qihao / Huang, Aibin / Zhang, Keyi / Wan, Shun / Chen, Hongyi / Fu, Yuntian / Zuo, Wusheng / Wang, Yongzhe / Cao, Xun / Wang, Lianjun / Lemmer, Uli / Jiang, Wan

    Nature communications

    2024  Band 15, Heft 1, Seite(n) 2141

    Abstract: Flexible thermoelectric devices show great promise as sustainable power units for the exponentially increasing self-powered wearable electronics and ultra-widely distributed wireless sensor networks. While exciting proof-of-concept demonstrations have ... ...

    Abstract Flexible thermoelectric devices show great promise as sustainable power units for the exponentially increasing self-powered wearable electronics and ultra-widely distributed wireless sensor networks. While exciting proof-of-concept demonstrations have been reported, their large-scale implementation is impeded by unsatisfactory device performance and costly device fabrication techniques. Here, we develop Ag
    Sprache Englisch
    Erscheinungsdatum 2024-03-08
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-024-46183-1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Bi

    Wu, Gang / Zhang, Qiang / Tan, Xiaojian / Fu, Yuntian / Guo, Zhe / Zhang, Zongwei / Sun, Qianqian / Liu, Yan / Shi, Huilie / Li, Jingsong / Noudem, Jacques G / Wu, Jiehua / Liu, Guo-Qiang / Sun, Peng / Hu, Haoyang / Jiang, Jun

    Advanced materials (Deerfield Beach, Fla.)

    2024  , Seite(n) e2400285

    Abstract: Bismuth-telluride-based alloy has long been considered as the most promising candidate for low-grade waste heat power generation. However, optimizing the thermoelectric performance of n-type ... ...

    Abstract Bismuth-telluride-based alloy has long been considered as the most promising candidate for low-grade waste heat power generation. However, optimizing the thermoelectric performance of n-type Bi
    Sprache Englisch
    Erscheinungsdatum 2024-04-12
    Erscheinungsland Germany
    Dokumenttyp Journal Article
    ZDB-ID 1474949-X
    ISSN 1521-4095 ; 0935-9648
    ISSN (online) 1521-4095
    ISSN 0935-9648
    DOI 10.1002/adma.202400285
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

    Volltext online

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  4. Artikel: Single cell and spatial alternative splicing analysis with long read sequencing.

    Fu, Yuntian / Kim, Heonseok / Adams, Jenea I / Grimes, Susan M / Huang, Sijia / Lau, Billy T / Sathe, Anuja / Hess, Paul / Ji, Hanlee P / Zhang, Nancy R

    Research square

    2023  

    Abstract: Long-read sequencing has become a powerful tool for alternative splicing analysis. However, technical and computational challenges have limited our ability to explore alternative splicing at single cell and spatial resolution. The higher sequencing error ...

    Abstract Long-read sequencing has become a powerful tool for alternative splicing analysis. However, technical and computational challenges have limited our ability to explore alternative splicing at single cell and spatial resolution. The higher sequencing error of long reads, especially high indel rates, have limited the accuracy of cell barcode and unique molecular identifier (UMI) recovery. Read truncation and mapping errors, the latter exacerbated by the higher sequencing error rates, can cause the false detection of spurious new isoforms. Downstream, there is yet no rigorous statistical framework to quantify splicing variation within and between cells/spots. In light of these challenges, we developed Longcell, a statistical framework and computational pipeline for accurate isoform quantification for single cell and spatial spot barcoded long read sequencing data. Longcell performs computationally efficient cell/spot barcode extraction, UMI recovery, and UMI-based truncation- and mapping-error correction. Through a statistical model that accounts for varying read coverage across cells/spots, Longcell rigorously quantifies the level of inter-cell/spot versus intra-cell/ spot diversity in exon-usage and detects changes in splicing distributions between cell populations. Applying Longcell to single cell long-read data from multiple contexts, we found that intra-cell splicing heterogeneity, where multiple isoforms co-exist within the same cell, is ubiquitous for highly expressed genes. On matched single cell and Visium long read sequencing for a tissue of colorectal cancer metastasis to the liver, Longcell found concordant signals between the two data modalities. Finally, on a perturbation experiment for 9 splicing factors, Longcell identified regulatory targets that are validated by targeted sequencing.
    Sprache Englisch
    Erscheinungsdatum 2023-03-21
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.21203/rs.3.rs-2674892/v1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel ; Online: Giotto: a toolbox for integrative analysis and visualization of spatial expression data

    Dries, Ruben / Zhu, Qian / Dong, Rui / Eng, Chee-Huat Linus / Li, Huipeng / Liu, Gan / Fu, Yuntian / Zhao, Tianxiao / Sarkar, Arpan / Bao, Feng / George, Rani E. / Pierson, Nico / Cai, Long / Yuan, Guo-Cheng

    Genome biology. 2021 Dec., v. 22, no. 1 p.78-78

    2021  

    Abstract: Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The ... ...

    Abstract Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.
    Schlagwörter data collection ; genome ; proteomics ; spatial data ; transcriptomics
    Sprache Englisch
    Erscheinungsverlauf 2021-12
    Umfang p. 78.
    Erscheinungsort BioMed Central
    Dokumenttyp Artikel ; Online
    ZDB-ID 2040529-7
    ISSN 1474-760X
    ISSN 1474-760X
    DOI 10.1186/s13059-021-02286-2
    Datenquelle NAL Katalog (AGRICOLA)

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  6. Artikel ; Online: Giotto: a toolbox for integrative analysis and visualization of spatial expression data.

    Dries, Ruben / Zhu, Qian / Dong, Rui / Eng, Chee-Huat Linus / Li, Huipeng / Liu, Kan / Fu, Yuntian / Zhao, Tianxiao / Sarkar, Arpan / Bao, Feng / George, Rani E / Pierson, Nico / Cai, Long / Yuan, Guo-Cheng

    Genome biology

    2021  Band 22, Heft 1, Seite(n) 78

    Abstract: Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The ... ...

    Abstract Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.
    Mesh-Begriff(e) Computational Biology/methods ; Data Analysis ; Gene Expression Profiling/methods ; Image Processing, Computer-Assisted ; Immunohistochemistry/methods ; In Situ Hybridization/methods ; Organ Specificity/genetics ; Software ; Spatial Analysis ; Transcriptome
    Sprache Englisch
    Erscheinungsdatum 2021-03-08
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2040529-7
    ISSN 1474-760X ; 1474-760X
    ISSN (online) 1474-760X
    ISSN 1474-760X
    DOI 10.1186/s13059-021-02286-2
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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