Sentence examples for subcellular identification from inspiring English sources

The first session focused on the molecular and subcellular identification of radiation events.

A high degree of co-localization of A1R and P2Y1R has been found in rat hippocampus by immunofluorescence experiments but without cellular and subcellular identification (Yoshioka et al., 2002).

During this exercise we found several discrepancies about the information pertaining to subcellular localization, identification of the topology of a membrane protein and mapping of the cleavage sequence.

The study of parasitic protozoa using light and transmission electron microscopy has often been faced with difficulties in subcellular compartment identification.

We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches.

This is the most extensive in silico protein subcellular localization identification to date for Leptospira interrogans serovar Lai genome that may be useful in protein annotation, discovery of novel genes and understanding the biology of Leptospira.

We have performed the first focused comparison of genome-wide laboratory/proteomic and computational methods for subcellular localization identification, and show that PSORTb is the first computational method to attain a level of precision exceeding that of high-throughput laboratory approaches.

Specific anitibodies against Syntaxin6 1∶1000 (Mouse mAb #S55420 Transduction Labs), Calnexin 1∶1000 (Rabbit Polyclonal #SPA-860 STRESSGEN), E-cadherin 1∶2500 (Mouse #610181 BD Biosciences) and S6 ribosomal protein 1∶1000 (5G10) Rabbit mAb #2217 Cell Signaling) were used for identification of subcellular cell compartments in sucrose gradient fractions.

Cytochemical approaches have allowed the bona fide identification of subcellular compartments within whole cells.

Identification of subcellular localization patterns from fluorescence images using supervised machine learning methods has become an established method, with excellent results in its field of application.

For the identification and subcellular localization of neuropil aggregates, we employed the anti-ataxin-3 antibody [ 29] on select 100 μm cerebral and brainstem sections (see Table  2 for a list of the primary antibodies).