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The false discovery rate (FDR) of protein identification was controlled using a target-decoy searching strategy (Elias and Gygi, 2007) where forward and reverse sequences from a database were in equal competition to be the highest ranking identification for each spectrum.
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Finally, we compare the performance of the low-rank identification methodology with other identification algorithms.
Aiming at reducing the complexity, we developed novel reduced-rank identification of principal components (RIPC) algorithms.
From the results, the B-LDA-MPCA algorithm has achieved the best rank 1 and rank 5 recognition results on all probes except the rank 1 identification rate on probe B and the rank 5 identification rate on probe D, demonstrating its superior recognition performance.
Bayesian network meta-analysis of root coverage procedures: ranking efficacy and identification of best treatment.
Phase-wise risk identification, ranking and analysis using traditional FMEA and fuzzy FMEA are discussed in section four.
Compared to the MPCA+LDA algorithm, the B-LDA-MPCA algorithm has improved the rank 1 identification rate by an average of and the rank 5 identification rate by an average of.
The rank 1 and rank 5 identification rates are used for recognition performance evaluation, where rank results report the percentage of probe subjects whose true match in the gallery set was in the top matches [10].
a Rank 1 identification rate.
Moreover, we calculated rank 1 identification rate as a criterion of the identification capability.
Fig. 7 Rank-1 identification rate and z-EERs for the difficulty level of CS labels.
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CEO of Professional Science Editing for Scientists @ prosciediting.com