Sentence examples for multiple prediction programs from inspiring English sources

This missense Arg258Gln mutation that localizes in exon 5, within the Sac1 domain of the protein, is predicted to be damaging by multiple prediction programs, and the arginine in position 258 is conserved in thirteen SYNJ1 orthologs and five Sac1-like domains containing proteins [ 3, 4].

The Database for Nonsynonymous SNPs' Functional Predictions (dbNSFP) (30) has recently been developed to collate these disparate results and provide a resource wherein a particular variant may be queried across multiple prediction programs.

This is to be expected based simply on the many clock regulated genes reported to date, the possibility that a single miRNA can target many different transcripts and the use of multiple prediction programs.

To infer dual targeting and to predict which subcellular destinations were shared, we first determined the single most likely subcellular destination for each protein based on information from multiple prediction programs.

The development of many different TM-helix prediction algorithms and the recent upsurge of GPCR structures (for a review, please see Venkatakrishnan and coworkers 42) have prompted us to consult multiple prediction programs and alternate templates for TM-helix prediction and in homology modeling, respectively.

TOPCONS uses multiple TMD prediction programs: SCAMPI-seq and SCAMPI-msa [ 25], PRODIV and PRO [ 26] and OCTOPUS [ 27].

To predict target genes, which may be co-regulated by the 3 concordant miRs, we used miRGator, an on-line interface that uses multiple target prediction programs.

An initial gene set was generated by using EvidenceModeler (Haas et al. 2008) to select the best gene call for a given locus from multiple gene prediction programs and PASA RNA-Seq transcripts as previously described (Haas et al. 2008, 2011).

In order to identify putative miR-187 targets we used miRWalk[ 14], a database that compiles results from multiple commonly used prediction programs (TargetScan, miRanda, miRDB and RNA22).

Because multiple in silico gene prediction programs were used in v1.1, gene models were manually examined for possible structural annotation errors, and to select alternate models if necessary.

Different subcellular and structure prediction programs predict different properties.