Astrocyte Regional Heterogeneity Revealed Through Machine Learning-based Glial Neuroanatomical Assays

被引：0
|
作者：
Blackburn, Jessica [1 ]
Alves, Michele [1 ]
Zhao, Jing [1 ]
Czeisler, Catherine [1 ]
Otero, Jose [1 ]
机构：
[1] Ohio State Univ, Columbus, OH 43210 USA
来源：
FASEB JOURNAL | 2020年 / 34卷
关键词：
D O I：
10.1096/fasebj.2020.34.s1.03912
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
引用
收藏
页数：2
相关论文
共 50 条
  • [1] Astrocyte regional heterogeneity revealed through machine learning-based glial neuroanatomical assays
    Blackburn, Jessica
    Alves, Michele Joana
    Aslan, Mehmet Tahir
    Cevik, Lokman
    Zhao, Jing
    Czeisler, Catherine M.
    Otero, Jose Javier
    JOURNAL OF COMPARATIVE NEUROLOGY, 2021, 529 (10) : 2464 - 2483
  • [2] Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods
    Honnorat, Nicolas
    Dong, Aoyan
    Meisenzahl-Lechner, Eva
    Koutsouleris, Nikolaos
    Davatzikos, Christos
    SCHIZOPHRENIA RESEARCH, 2019, 214 : 43 - 50
  • [3] The neuroanatomical pattern of sex and gender in cis/transgender individuals revealed by machine learning-based pattern recognition with NeuroMiner
    Baldinger, P.
    Castro, M. F. Urquijo
    Seiger, R.
    Kranz, G. S.
    Spies, M.
    Kaufmann, U.
    Windischberger, C.
    Kasper, S.
    Falkai, P.
    Koutsouleris, N.
    Lanzenberger, R.
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2019, 29 : S306 - S307
  • [4] Spatial heterogeneity of the cytosol revealed by machine learning-based 3D particle tracking
    McLaughlin, Grace A.
    Langdon, Erin M.
    Crutchley, John M.
    Holt, Liam J.
    Forest, M. Gregory
    Newby, Jay M.
    Gladfelter, Amy S.
    MOLECULAR BIOLOGY OF THE CELL, 2020, 31 (14) : 1498 - 1511
  • [5] Machine learning-based assessment of intratumor heterogeneity in glioblastoma
    Hieber, D.
    Prokop, G.
    Karthan, M.
    Maerkl, B.
    Schlegel, J.
    Pryss, R.
    Grambow, G.
    Schobel, J.
    Liesche-Starnecker, F.
    BRAIN PATHOLOGY, 2023, 33
  • [6] Analytical Needs for Machine Learning-based Image Analysis of Brainstem Astrocyte Cell Function
    Blackburn, Jessica
    Czeisler, Catherine M.
    Otero, Jose J.
    FASEB JOURNAL, 2022, 36
  • [7] Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays
    Vanderboom, Patrick M.
    Renuse, Santosh
    Maus, Anthony D.
    Madugundu, Anil K.
    V. Kemp, Jennifer
    Gurtner, Kari M.
    Singh, Ravinder J.
    Grebe, Stefan K.
    Pandey, Akhilesh
    Dasari, Surendra
    JOURNAL OF PROTEOME RESEARCH, 2022, 21 (08) : 2045 - 2054
  • [8] Machine learning-based regional flood frequency analysis of Indian watersheds
    Mangukiya, Nikunj K.
    Kumar, Abhishek
    Sharma, Ashutosh
    CLEAN-SOIL AIR WATER, 2025, 53 (03)
  • [9] Explaining landscape preference heterogeneity using machine learning-based survey analysis
    Liu, Xiaozi
    Tvinnereim, Endre
    Grimsrud, Kristine M.
    Lindhjem, Henrik
    Velle, Liv Guri
    Saure, Heidi Iren
    Lee, Hanna
    LANDSCAPE RESEARCH, 2021, 46 (03) : 417 - 434
  • [10] Machine learning-based assessment of the impact of the manufacturing process on battery electrode heterogeneity
    Duquesnoy, Marc
    Boyano, Iker
    Ganborena, Larraitz
    Cereijo, Pablo
    Ayerbe, Elixabete
    Franco, Alejandro A.
    ENERGY AND AI, 2021, 5
12345