Sentence examples for computational data analysis from inspiring English sources

"Bioinformatics" or "computational biology" makes extensive use of information-theoretic measures, as part of the attempt to use sophisticated computational data analysis tools on biological problems.

The combination of solid conceptual underpinnings and tools for its use have made the GO a widely popular resource in the biological and bioinformatics research community and an essential resource for computational data analysis.

After a discussion of advantages and disadvantages of oligonucleotide probes in comparison to amplicons, this chapter focuses on recent advances and remaining key challenges in probe design and computational data analysis for spotted and in situ‐synthesized oligonucleotide microarray technologies.

Using computational data analysis, Hughes hopes to create evolutionary trees of these genes and regulatory mechanisms in order to figure out how they work together to make cells function and how they contribute to the physiology of the organisms they are found in.

To meet this challenge the medicinal chemist's toolbox has expanded over the years to include, high-throughput screening, computer-aided design, X-ray crystallography, target protein mutagenesis, combinatorial and automated chemistry, QSAR, chemical property calculations, computational data analysis, high-throughput ADME assays.

Interestingly, these results correlated better with the relaxed p<0.05 criteria and, therefore, point to a general caveat in computational data analysis of determining appropriate cut-offs.

This offers researchers and R&D professionals, with limited-to-no computational and data analysis training, and their corresponding organisations (ie. pharmaceutical companies), a highly scalable, modular and reproducible system that automates the analysis processes, learns from the data and provides actionable insights.

Considerable intellectual support, computational and data analysis tools were provided by Adam Arkin, Katherine Huang, Morgan Price, Eric Alm, Dan Kirshner, and Kimmen Sjölander – sufficient gratitude cannot be expressed for their generous help.

It is now easy to generate genome-wide scans with more than one million SNPs (single nucleotide polymorphisms) but these huge databases pose challenges in computational capacity, data analysis and interpretation of results for genomic selection [ 2].

Conference topics included statistical methods, quantitative molecular data sets, computational algorithms for data analysis, computational modeling and simulation, challenges and opportunities in computational biology, and information technology infrastructure for data and tool management.

A microarray can produce a massive amount of data and require high computational power for data analysis.