Automated subcellular location determination and high-throughput microscopy.

By E. Glory, Robert F. Murphy. Developmental Cell, 2007

296 citations recorded by the source corpus.

Subfields: Biophysics, Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/895beab20b3a1d89e45a74b83119b737bd3d4dd4

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In Biophysics

In Computer Vision and Pattern Recognition

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Citations in the corpus

Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization (2010, background): “Information of the subcellular localization of proteins is important because it can (1) indicate how and under what kind of cellular environments they interact with each other and with other molecules, (2) provide useful clues for revealing their functions, and (3) help understand the intricate path”
Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms (2010, background): “Proteins with multiple location sites or dynamic feature of this kind are particularly interesting because they may have some unique biological functions worthy of our special notice [2,3].”
Local binary patterns variants as texture descriptors for medical image analysis (2010, background): “Recent work focused on training generic classifiers using image descriptors [36,37].”
Biological Imaging Software Tools (2012, background): “Biologists are increasingly interested in using image analysis to convert microscopy images into quantitative data 15,16 .”
Recent progress in protein subcellular location prediction. (2007, background): “Although most proteins are of a single location, some may simultaneously exist at, or move between, two or more different subcellular locations [40].”
Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms (2008, background): “…because it can (i) provide useful insights about their functions, (ii) indicate how and in what kind of cellular environments they interact with each other and with other molecules and (iii) help in understanding the intricate pathways that regulate biological processes at the cellular level 1,2 .”
CP-CHARM: segmentation-free image classification made accessible (2016, methodology): “Recently, several whole image-based methods have been proposed for particular biological imaging classification problems such as protein subcellular localization [3–5] and immunostaining pattern identification [6].”
A New Method for Predicting the Subcellular Localization of Eukaryotic Proteins with Both Single and Multiple Sites: Euk-mPLoc 2.0 (2010, unknown): “Actually, proteins with multiple locations or dynamic feature of this kind are particularly interesting because they may have some very special biological functions worthy of our notice [11,12].”
iLoc-Euk: A Multi-Label Classifier for Predicting the Subcellular Localization of Singleplex and Multiplex Eukaryotic Proteins (2011, background): “(3) It can help our understanding of the intricate pathways that regulate biological processes at the cellular level [1,2] and hence it is indispensable for many studies in system biology.”