Developmental mouse brain common coordinate framework

Autor: Fae N. Kronman, Josephine K. Liwang, Rebecca Betty, Daniel J. Vanselow, Yuan-Ting Wu, Nicholas J. Tustison, Ashwin Bhandiwad, Steffy B. Manjila, Jennifer A. Minteer, Donghui Shin, Choong Heon Lee, Rohan Patil, Jeffrey T. Duda, Jian Xue, Yingxi Lin, Keith C. Cheng, Luis Puelles, James C. Gee, Jiangyang Zhang, Lydia Ng, Yongsoo Kim

Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)

Abstract 3D brain atlases are key resources to understand the brain’s spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders

Externí odkaz: https://doaj.org/article/a5b5166d34af4240a02ab1939e81a491

Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections

Autor: Kaitlin M. Stouffer, Alain Trouvé, Laurent Younes, Michael Kunst, Lydia Ng, Hongkui Zeng, Manjari Anant, Jean Fan, Yongsoo Kim, Xiaoyin Chen, Mara Rue, Michael I. Miller

Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-22 (2024)

Abstract This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging tec

Externí odkaz: https://doaj.org/article/437796a99edd427faec35dd8a7032d20

Automated Pavement Condition Index Assessment with Deep Learning and Image Analysis: An End-to-End Approach

Autor: Eldor Ibragimov, Yongsoo Kim, Jung Hee Lee, Junsang Cho, Jong-Jae Lee

Publikováno v: Sensors, Vol 24, Iss 7, p 2333 (2024)

The degradation of road pavements due to environmental factors is a pressing issue in infrastructure maintenance, necessitating precise identification of pavement distresses. The pavement condition index (PCI) serves as a critical metric for evaluati

Externí odkaz: https://doaj.org/article/dd6191b6dc104f49896e56de52aaa99a

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Autor: Michael Hawrylycz, Maryann E Martone, Giorgio A Ascoli, Jan G Bjaalie, Hong-Wei Dong, Satrajit S Ghosh, Jesse Gillis, Ronna Hertzano, David R Haynor, Patrick R Hof, Yongsoo Kim, Ed Lein, Yufeng Liu, Jeremy A Miller, Partha P Mitra, Eran Mukamel, Lydia Ng, David Osumi-Sutherland, Hanchuan Peng, Patrick L Ray, Raymond Sanchez, Aviv Regev, Alex Ropelewski, Richard H Scheuermann, Shawn Zheng Kai Tan, Carol L Thompson, Timothy Tickle, Hagen Tilgner, Merina Varghese, Brock Wester, Owen White, Hongkui Zeng, Brian Aevermann, David Allemang, Seth Ament, Thomas L Athey, Cody Baker, Katherine S Baker, Pamela M Baker, Anita Bandrowski, Samik Banerjee, Prajal Bishwakarma, Ambrose Carr, Min Chen, Roni Choudhury, Jonah Cool, Heather Creasy, Florence D'Orazi, Kylee Degatano, Benjamin Dichter, Song-Lin Ding, Tim Dolbeare, Joseph R Ecker, Rongxin Fang, Jean-Christophe Fillion-Robin, Timothy P Fliss, James Gee, Tom Gillespie, Nathan Gouwens, Guo-Qiang Zhang, Yaroslav O Halchenko, Nomi L Harris, Brian R Herb, Houri Hintiryan, Gregory Hood, Sam Horvath, Bingxing Huo, Dorota Jarecka, Shengdian Jiang, Farzaneh Khajouei, Elizabeth A Kiernan, Huseyin Kir, Lauren Kruse, Changkyu Lee, Boudewijn Lelieveldt, Yang Li, Hanqing Liu, Lijuan Liu, Anup Markuhar, James Mathews, Kaylee L Mathews, Chris Mezias, Michael I Miller, Tyler Mollenkopf, Shoaib Mufti, Christopher J Mungall, Joshua Orvis, Maja A Puchades, Lei Qu, Joseph P Receveur, Bing Ren, Nathan Sjoquist, Brian Staats, Daniel Tward, Cindy T J van Velthoven, Quanxin Wang, Fangming Xie, Hua Xu, Zizhen Yao, Zhixi Yun, Yun Renee Zhang, W Jim Zheng, Brian Zingg

Publikováno v: PLoS Biology, Vol 21, Iss 6, p e3002133 (2023)

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell typ

Externí odkaz: https://doaj.org/article/5683e726eb424a3187544a44691a1d0f

Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data

Autor: Bárbara Andrade Barbosa, Saskia D. van Asten, Ji Won Oh, Arantza Farina-Sarasqueta, Joanne Verheij, Frederike Dijk, Hanneke W. M. van Laarhoven, Bauke Ylstra, Juan J. Garcia Vallejo, Mark A. van de Wiel, Yongsoo Kim

Publikováno v: Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)

Deconvolution methods reveal individual cell types in complex tissues profiled by bulk methods. Here the authors present a Bayesian deconvolution method that outperforms existing methods when benchmarked on >700 datasets, especially in estimating cel

Externí odkaz: https://doaj.org/article/ab00233eafcc4cf68cdbf4b21d5d6744