scholarly journals High-throughput subcellular protein localization using cell arrays

2005 ◽  
Vol 33 (6) ◽  
pp. 1407 ◽  
Author(s):  
D. Vanhecke ◽  
Y.-H. Hu ◽  
H. Lehrach ◽  
M. Janitz
Keyword(s):  
High Throughput ◽  
Protein Localization ◽  
Subcellular Protein Localization ◽  
Cell Arrays

scholarly journals High-throughput subcellular protein localization using cell arrays

2005 ◽  
Vol 33 (6) ◽  
pp. 1407-1408 ◽  
Author(s):  
Y.-H. Hu ◽  
D. Vanhecke ◽  
H. Lehrach ◽  
M. Janitz
Keyword(s):  
High Throughput ◽  
Cellular Localization ◽  
Fluorescent Protein ◽  
Protein Localization ◽  
Open Reading Frames ◽  
Expression Vectors ◽  
Sequence Information ◽  
Cell Array ◽  
Single Experiment ◽  
Cell Arrays

Accomplishment of the human and mouse genome projects resulted in accumulation of extensive gene sequence information. However, the information about the biological functions of the identified genes remains a bottleneck of the post-genomic era. Hence, assays providing simple functional information, such as localization of the protein within the cell, can be very helpful in the elucidation of its function. Transfected cell arrays offer a robust platform for protein localization studies. Open reading frames of unknown genes can be linked to a His6-tag or GFP (green fluorescent protein) reporter in expression vectors and subsequently transfected using the cell array. Cellular localization of the transfected proteins is detected either by specific anti-His-tag antibodies or directly by fluorescence of the GFP fusion protein and by counterstaining with organelle-specific dyes. The high throughput of the method in terms of information provided for every single experiment makes this approach superior to classical immunohistological methods for protein localization.

scholarly journals Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 264
Author(s):  
Kaisa Liimatainen ◽  
Riku Huttunen ◽  
Leena Latonen ◽  
Pekka Ruusuvuori
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Convolutional Neural Network ◽  
High Throughput ◽  
Protein Function ◽  
Protein Localization ◽  
Convolutional Network ◽  
High Throughput Analysis ◽  
Fully Convolutional Network

Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to assess protein localizations, with increasing demand of automated high throughput analysis methods to supplement the technical advancements in high throughput imaging. Here, we study the applicability of deep neural network-based artificial intelligence in classification of protein localization in 13 cellular subcompartments. We use deep learning-based on convolutional neural network and fully convolutional network with similar architectures for the classification task, aiming at achieving accurate classification, but importantly, also comparison of the networks. Our results show that both types of convolutional neural networks perform well in protein localization classification tasks for major cellular organelles. Yet, in this study, the fully convolutional network outperforms the convolutional neural network in classification of images with multiple simultaneous protein localizations. We find that the fully convolutional network, using output visualizing the identified localizations, is a very useful tool for systematic protein localization assessment.

scholarly journals High-throughput single cell arrays as a novel tool in biopreservation

Cryobiology ◽  
2009 ◽  
Vol 58 (3) ◽  
pp. 315-321 ◽  
Author(s):  
Kenneth L. Roach ◽  
Kevin R. King ◽  
Korkut Uygun ◽  
Steven C. Hand ◽  
Isaac S. Kohane ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Cell Arrays

TheArabidopsis Localizome: Subcellular Protein Localization and Interactions inARABIDOPSIS

2008 ◽  
pp. 61-81
Author(s):  
Georgios Kitsios ◽  
Nicolas Tsesmetzis ◽  
Max Bush ◽  
John H. Doonan
Keyword(s):  
Protein Localization ◽  
Subcellular Protein Localization

Barcodes for subcellular protein localization

2019 ◽  
Vol 3 (9) ◽  
pp. 673-675 ◽  
Author(s):  
Yizhe Zhang ◽  
Alden Moss ◽  
Kristine Tan ◽  
Amy E. Herr
Keyword(s):  
Protein Localization ◽  
Subcellular Protein Localization
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