Through representation of protein structures as PB sequence, conformational similarity could be identified for 159,780 (74%) variable segments, based on PB scores, an increase by 21%, compared to a classical structural alignment approach in the database of structurally aligned homologous protein structures.
Our ability to identify TIC events with high sensitivity using short reads highlights the utility of a targeted alignment approach in dealing with RNA-Seq data.
Difficulties in detecting DS relationships for conventional structural alignment approaches originate in the nature of the algorithms.
Their method, unlike the forced-alignment approach in [11] which uses beam pruning to identify erroneous matches, could find also the correct sequence and not only the best match in terms of the state sequence between the text and audio chunk.
Herein, we describe our anchored-alignment approach in detail using a previously introduced set-theoretical alignment concept.
A comparison table of asymptotic time and space complexity of a number of modern RNA simultaneous folding and alignment approaches is shown in Table 1.
In addition, in contrast to the seed-path extension method used by NetworkBLAST-M, our method is similar to the star aligned approach in multiple sequence alignment introduced by Lipman et al. (1989) and CLUSTAL W (Thompson et al., 1994).
Among the various algorithms for aligning multiple sequences, we selected the alignment approach implemented in the PRANK program [16].
In this paper, we show that both the targeted alignment and spliced alignment approaches can be used in complementary ways to study TICs and gene fusions in individual cancer and normal samples assayed by deep transcriptional sequencing.
In contrast to sequence alignment approaches, gap penalties are not included in the calculation of E -values, since structurally similar residues on a protein surface may by definition, be quite separate in the protein sequence.
