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Moreover, Hammock supports the concept of sequence labels.
The motivation for sequence labels is to offer the possibility of structuring datasets.
During the deconvolution, the site information (e.g. plot and subplot name) was added into the sequence labels for later analysis.
Once the model is built, it can be used to predict the most likely sequence labels for new sequences.
The method first learns the model's parameters on a training dataset of array-CGH sequences with known sequence labels.
From the upstream and downstream sequence labels it is easy to study the conservation of the gene pair, using the BLAST button.
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Sequence labeling: There is a somewhat arbitrary line between the preceding task and sequence labeling.
Yu et al. [19] proposed a deep-structured CRF for sequence labelling.
In this study, the CHEMDNER task is formulated as a sequence labelling problem.
We consider named entity recognition as a combination of two problems: segmentation and sequence labelling.
We considered the chemical compound and drug name recognition as a sequence labeling problem.
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