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Although many such models exist, most of the top-scoring ML-based tools submitted for the CHEMDNER task utilised conditional random fields (CRF), which are traditionally used for sequence labelling.
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Conditional Random Fields (CRFs) are probabilistic graphical models widely used for sequence labeling problems in general and NER in particular because they often achieve high performance [ 4, 10, 22].
In a linear chain CRF, which is used for sequence modeling tasks, the label y i at position i depends on its predecessor y i -1 and successor y i +1.
Amino acid residues that interact with the uridine are labeled and shown in stick representation and were used for sequence identity calculation with hCNTs.
Traditional BIO labels are used for the sequence labelling.
In addition to the five types, an 'unknown' label is used for sequences with scores lower that these cutoffs but still high enough to safely predict the sequence as an SDR: 'classical' — 29, 'extended' — 75, and 'divergent' — 100.
SequiTherm Excel ™ sequencing kits (Epicentre Technologies) and infrared labeled primers were used for sequencing reactions.
The same labeled primer was also used for sequencing with the fmol® DNA Cycle Sequencing System (Promega).
Open reading frames (ORFs) were initially labeled with "Y" for yeast, alphabetical letters for chromosome (such as C for chromosome III), labeled with "L" or "R" for the left or right chromosome arm, and labeled with sequential numbers indicating their order within the specific plasmid or cosmid clone used for sequencing (B. Dujon, personal communication).
PCR primers were used for sequencing.
The extracts were further used for sequencing.
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