Sentence examples for biological data are often from inspiring English sources

In the deep sea, biological data are often sparse; hence models capturing relationships between observed fauna and environmental variables (acquired via acoustic mapping techniques) are often used to produce full coverage species assemblage maps.

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales.

Third, biological data are often rare and difficult to obtain.

However, computational methods that can handle the complexity (noisy, substantial amount of variables, high dimensionality, etc). of these biological data are often unavailable [ 1].

Biological data are often organized into matrices in which the rows signify different items of interest (a gene, a subject, a probe or a position in a sequence), while the columns describe different experiments, variations, or samples.

Unfortunately, the parameter estimation from biological data is often underdetermined, where many parameter combinations could fit the data equally well [ 3, 4].

It highlights an essential difference in the two methods since biological data is often repetitive, but with a wide range of oscillatory patterns.

Human biological samples and medical data are often provided as donations (opt-in donations) or as residual material, and the motivation of their provision is seen as to contribute to the common good.

Biological data, like the PPI data, are often observed in an incomplete manner with high noise.

High-dimensional biological data, such as microarray profiling data, are often interpreted as being composed of sets of transcriptional- or activity programs that explain some, or most, of the complexity in the data [ 6- 8].

Nanomaterial interactions with biological systems are complex and, accordingly, associated data are often generated at multiple levels of detail.