Literature DB >> 27207361

Seeing Is Believing: Quantifying Is Convincing: Computational Image Analysis in Biology.

Ivo F Sbalzarini1,2,3.   

Abstract

Imaging is center stage in biology. Advances in microscopy and labeling techniques have enabled unprecedented observations and continue to inspire new developments. Efficient and accurate quantification and computational analysis of the acquired images, however, are becoming the bottleneck. We review different paradigms of computational image analysis for intracellular, single-cell, and tissue-level imaging, providing pointers to the specialized literature and listing available software tools. We place particular emphasis on clear categorization of image-analysis frameworks and on identifying current trends and challenges in the field. We further outline some of the methodological advances that are required in order to use images as quantitative scientific measurements.

Mesh:

Year:  2016        PMID: 27207361     DOI: 10.1007/978-3-319-28549-8_1

Source DB:  PubMed          Journal:  Adv Anat Embryol Cell Biol        ISSN: 0301-5556            Impact factor:   1.231


  10 in total

Review 1.  Imaging morphogenesis.

Authors:  Donald M Bell
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-05-19       Impact factor: 6.237

2.  DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae.

Authors:  Ying Zhang; Yubin Xie; Wenzhong Liu; Wankun Deng; Di Peng; Chenwei Wang; Haodong Xu; Chen Ruan; Yongjie Deng; Yaping Guo; Chenjun Lu; Cong Yi; Jian Ren; Yu Xue
Journal:  Autophagy       Date:  2019-06-20       Impact factor: 16.016

3.  Probabilistic spatial analysis in quantitative microscopy with uncertainty-aware cell detection using deep Bayesian regression.

Authors:  Alvaro Gomariz; Tiziano Portenier; César Nombela-Arrieta; Orcun Goksel
Journal:  Sci Adv       Date:  2022-02-04       Impact factor: 14.136

Review 4.  Bioprocess microfluidics: applying microfluidic devices for bioprocessing.

Authors:  Marco Pc Marques; Nicolas Szita
Journal:  Curr Opin Chem Eng       Date:  2017-11       Impact factor: 5.163

Review 5.  What Drives Symbiotic Calcium Signalling in Legumes? Insights and Challenges of Imaging.

Authors:  Teresa Vaz Martins; Valerie N Livina
Journal:  Int J Mol Sci       Date:  2019-05-07       Impact factor: 5.923

6.  Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila.

Authors:  Sebastian M Bernasek; Nicolás Peláez; Richard W Carthew; Neda Bagheri; Luís A N Amaral
Journal:  PLoS Comput Biol       Date:  2020-03-03       Impact factor: 4.475

7.  Quantitative analysis of subcellular distributions with an open-source, object-based tool.

Authors:  Pearl V Ryder; Dorothy A Lerit
Journal:  Biol Open       Date:  2020-10-19       Impact factor: 2.422

Review 8.  Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain.

Authors:  Kyra T Newmaster; Fae A Kronman; Yuan-Ting Wu; Yongsoo Kim
Journal:  Front Neuroanat       Date:  2022-01-14       Impact factor: 3.856

Review 9.  A Spotlight on Viruses-Application of Click Chemistry to Visualize Virus-Cell Interactions.

Authors:  Thorsten G Müller; Volkan Sakin; Barbara Müller
Journal:  Molecules       Date:  2019-01-29       Impact factor: 4.411

Review 10.  Dissecting Neuronal Activation on a Brain-Wide Scale With Immediate Early Genes.

Authors:  Alessandra Franceschini; Irene Costantini; Francesco S Pavone; Ludovico Silvestri
Journal:  Front Neurosci       Date:  2020-10-23       Impact factor: 4.677

  10 in total

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