Sentence examples for transcript algorithm from inspiring English sources
Our seven-gene transcript algorithm suggests that 8 21%% of patients with primary breast cancers may respond to olaparib and that the responsive tumors are enriched in basal-like breast cancers.
This transcript algorithm compares favourably with existing Cufflinks and Scripture algorithms with respect to memory usage (2 Gb cf. to 6 Gb) and feature identification (Supplementary Fig. S1 and Table S1), with a number of novel features validated using RT-PCR (Supplementary Fig. 2).
Briefly, the Transcripts algorithm provides comprehensive transcript identification even in complex mammalian genomes, the TSS algorithm predicts transcription start sites and UTR algorithm specifically identifies expressed 3′-UTRs to facilitate downstream miRNA-binding site prediction analysis.
Once the hypothesis is aligned with the transcript, the algorithm estimates the matching transcript-to-hypothesis score (denoted ).
This indicates that the sliding window transcript detection algorithm has a high sensitivity for ncRNA transcripts.
For each transcript, our algorithm recorded the "height" (Euclidian distance) between the clusters.
Tiling Assembly is a heuristic, ab initio transcript assembly algorithm, which uses a read tiling approach to identify transcripts.
To overcome these shortcomings, a heuristic ab initio transcript assembly algorithm, Tiling Assembly, was developed to identify genes based on short read and junction alignment.
Based on a detailed analysis of the problem and of previous work, we identified three important requirements that a transcript inference algorithm based on RNA-Seq data should meet.
Due to the use of similarity information between two related organisms to extend transcripts, our algorithm cannot identify extended transcripts that are not shared between the two organisms.
However, transcript inference algorithms rely on heuristics to resolve the transcript structure, because the inference problem is, in general, underdetermined.
