Sentence examples for biological data is often from inspiring English sources

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.

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.

The estimation of ODE model parameters from time-series data is often the bottlenecking step in biological system modeling.

Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples.

Compounding these difficulties, time series or perturbation data is often difficult to obtain, either for ethical or technical reasons, from human in vivo biological states.

Data is often hidden or encrypted.