Sentence examples for method that labels from inspiring English sources

Multicolor flp-out (MCFO) is a stochastic method that labels individual cells in different colors using a set of three UAS-STOP-epitope constructs that each expresses a different epitope when the STOP cassette is removed.

Multicolor flp-out (MCFO; Figure 1G) is a stochastic method that labels individual cells in different colors using a set of three UAS-STOP-epitope constructs that each expresses a different epitope when the STOP cassette is removed.

These include simple indexing methods that label events of interests for easy retrieval to virtual environments that artificially render the events in the scene.

However, methods that label viral envelopes or virion surface proteins can be used only to visualize viral attachment, early entry, or late assembly.

To further examine whether lovastatin is regulating the internalization of the VEGFR ligand complex, we performed the Pinpoint Cell Surface Protein Isolation method that specifically labels and isolates proteins found on the cell surface.

To obtain direct evidence for neuronal degeneration in the spinal cord, we used a silver staining method that selectively labels degenerating neurons and their processes (Fig.  4).

Gallyas method is one of the most "sensitive" silver-staining method that clearly labels NFTs of AD, as well as neuronal and glial lesions of corticobasal degeneration/progressive supranuclear palsy (CBD/PSP) [ 113, 120].

Here, we describe a genetic method that allows labeling of a single neuron or small subsets of neurons with one fluorescent marker while simultaneously labeling their pre-synaptic terminals with a different fluorescent marker.

We developed a modified Nissl staining method that quickly labeled the cells and blood vessels simultaneously in an entire mouse brain.

Data-independent, alternate-scanning LC-MS is an ion current based mass spectrometric analysis method that offers label-free quantification of molar protein abundances [11], [12].

Input: set of documents D, thresholds κ1, κ2 Output: set of probability models P Anchor(D) (1) P ← ∅ (2) W ← LDA n(D) (3) foreach i = 1... n (4)     L i ← { d ∈ D| w i(d) > κ1} (5)     L −i ← { d ∈ D| w i(d) ≤ κ2} (6)     p i ← train(L i, L −i) (7)     P ← P ∪ { p i} (8) return P or proportions and where line (6) can be replaced with any supervised method that uses the labels L i, i = 1... n.