Sentence examples for several gene models from inspiring English sources

Searches of the sea urchin genome show several gene models encoding putative ligands and signaling proteins that might interact with SpTie1/2.

In this study, we have developed a platform for performing and simulating BSA and XAM with microarrays in several gene models, using the preferred SNP genotyping arrays for Arabidopsis.

Several gene models contain regions of unresolved sequence (e.g. N nucleotide designations) in middle of gene sequence (e.g. gene models coding for the 293291 or 298293 proteins) and/or unusually long introns regions (e.g. the model coding for the 298293 protein).

Using a custom-made set of highly discriminative sequence profiles we scanned a representative set of metazoan genomes and subsequently corrected several gene models.

We used custom-made Hidden Markov Models (HMMs), corrected several gene models of published genomes, resequenced Hydra-sequences, and thus revealed four previously unrecognized paralogs.

We excluded several gene models coding for proteins containing only one LIM domain linked to either a cytochrome P450 domain or an ubiquitin interaction motif and focused on gene models with two LIM domains.

Several gene knockout models mimic human processes and have provided valuable insight into the role of endogenous mediators in thermoregulatory processes.

Several thousand gene models were updated and/or reannotated leading to addition of 5′, 3′ or internal exons (for a complete overview of Xtev v3.4) known gene model update see Additional file 1: Figures S6 and S7a).

While several different gene models are put forward for each gene, the Fgenesh ab initio models (CtDlxa: fgenesh1_pg.C_scaffold_237000015, CtDlxb: fgenesh1_pg.C_scaffold_237000013) predict an intron-exon structure typical for Dlx genes (three exons, with the second intron located between amino acids 44 and 45 of the homeodomain, Figure 1).

Although several gene network modeling techniques have been applied to microarray data, including weight matrices [ 1], Boolean networks [ 2], and differential equations [ 3], Bayesian Networks (BNs), BN seemed to show the greatest promise in the analysis of expression data as they provided the ability to learn network structures and develop predictive models of system response [ 4].

Several laccase-encoding gene models and AA2 peroxidases (MnP, LiP or VP) were identified in P. cinnabarinus.