In agreement to this observation, the cell proliferation marker Ki-67 has been shown to label only a small minority of cells at the invasive front as compared to the more differentiated central part of the tumor, suggesting that non-proliferating tumor cells that have escaped the tumor mass could have metastatic potential [47].
In order to validate the performance of the algorithm in paucity of labeled data, only a small number of proteins are selected as labeled data, which makes the problem very challenging.
The labeling of nestin usually manifested as individual signals or small clusters of particles; filamentous structures were labeled only sporadically.
When we utilized the same astrocyte alrm -Gal4 driver to produce hMeCP2 in astrocyte alrm -Gal4P2 protein was drivered by antobody labeling in only a small number of astrocytes (290±23 (± s.e.m).) (Fig. 1F,F′,F″).
Analysts, however, have noted that some dairy products produced from cows that have not been injected with a bovine growth hormone produced in bacteria are labeled, and only a very small percentage of consumers seek them out.
We should also note that the 71G01-LexA driver used for GRASP only labels a small subset of pC1 neurons, while the intersection of 71G01-LexA andsxsx GAL4 actually labels a broader group of pC1 neurons.
Lines labeling only a subset of these MBONs gave only small effects when blocked.
It is likely that small changes in the size of the label string will have only a small effect on the set of reads which appear close together in the final ordering, and despite, the fact that a small change in the label length will change the number of buckets, we expect that it will have a substantially smaller change on the distance in the final order among sets of similar reads.
Because semi-supervised learning algorithms use both labeled and unlabeled instances in the training process, they can produce classifiers that achieve better performance than completely supervised learning algorithms that have only a small amount of labeled data available for training [ 1- 3].
The goal of Co-Training is to enhance performance of learning algorithm when only a small set of labeled examples is available.
