Sentence examples for based on sequence derived from inspiring English sources

Hence, developing a reliable in silico sumoylation prediction method that has a better accuracy based on sequence derived features, bears a significant importance for the understanding complex diseases, cellular processes and epigenetic mechanisms.

Gene-specific primers (5′-GAA GGC GGA CAT GTT GGT CGG GCA G-3′ and 5′-TGT GTC GTC CGA ACA GAA CAG CTG A-3′) were designed based on sequence derived from 5′-RACE and Ensembl database (Zv8).

The primer pairs for β-tub and lys2 were designed based on sequences derived from primers used in previous studies, respectively [ 16, 17].

We designed custom RNA bait libraries for targeting putatively single-copy orthologous genes based on sequences derived from seven shark species in [ 32], i.e. Chlamydoselachus anguineus, Etmopterus joungi, Isurus oxyrinchus, Orectolobus halei, Carcharhinus amblyrhynchos, Heterodontus portusjacksoni, and Squatina nebulosa.

Here, we applied a similarity network-based methodology for the representation and analysis of protein sequences and structures sets using a non-redundant set of 311 proteins and three different information criteria based on sequence-derived features, sequence local alignment and structural alignment.

Predictions are based on sequence-derived features.

The protein representation used in the binary classifiers is based on sequence-derived features (e.g. amino acid composition) and gene ontology (GO) terms.

Both WoLF PSORT and Euk-mPLoc represent proteins based on sequence-derived features, while Euk-mPLoc also uses relevant GO terms.

The protein representation used in IMMML is based on sequence-derived features (amino acid composition and pseudo-amino acid composition) and gene ontology (GO) terms.

Dense genetic maps based on sequence-derived markers allow finer comparative genome analyses to be performed based on comparisons with sequenced related genomes and to accelerate the process of map-based cloning of major genes and QTL.

The Binding site prediction by Maximum Likelihood (BindML) approach is based on sequence-derived evolutionary information, though it does use an input structure to choose patches of the query protein to target [ 12, 52].