Sentence examples for bioinformatics methods such as from inspiring English sources

Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis.

There is already considerable research in progress toward applying parallel computing techniques on bioinformatics methods, such as multiple sequence alignment, gene expression analysis and phylogenetic studies.

Based on such a consideration, several bioinformatics methods such as KEGG pathway analysis were employed in our study.

Hence, we characterized Glbs from 62 rhizobial genomes using bioinformatics methods such as data mining in databases, sequence alignment, phenogram construction and protein modeling.

Moreover, several powerful bioinformatics methods, such as co-expression analysis, text mining and ortholog interaction prediction, have been developed to assist in the global interactome analysis, making the interactome data more massive and complicated.

In this study, we predicted that vitamin B6 biosynthesis is the primary target of SPS1 by employing bioinformatics methods such as microarray and GO analyses and confirmed the prediction experimentally by showing that PLP levels were decreased by SPS1 knockdown and that the inhibition of PLP biosynthesis caused the same phenotypes as SPS1 knockdown.

The use of guide trees was a significant advance for multiple sequence alignment in sequence bioinformatics, and methods such as CLUSTAL-W 34) CLUSTAL-W 34 widespread popularity in nucleic acid and protein sequence alignment.

In this study, these issues were addressed by incorporation of advanced bioinformatics and conventional methods such as real-time PCR and immunohistochemistry.

In addition, bioinformatics database curation methods such as the use of evidence codes and citations to provide data provenance, and the incorporation of mini-review summaries that describe enzymes and pathways, benefit systems-biology models, which typically lack data provenance and explanations.

Despite their considerable merit, predictive bioinformatics tools or massively parallel methods such as microarrays remain limited by the need for knowledge of consensus or sequence which may not yet exist, and are sometime affected by false-positive [63] [65].

It does not rule out the possibility of more advanced methods, such as pathway-based analysis (e.g. Bioinformatics, 30(201489-196, 2014), may have a better chance of finding such biomarkers.