Sentence examples for multiple experimental methods from inspiring English sources

In this paper, pore structure, formation porosity, total organic carbon (TOC), thermal maturity, and mineralogy of 36 samples in Longmaxi shale and 7 samples in Qiongzhusi shale have been investigated using multiple experimental methods.

A thorough investigation using multiple experimental methods is prudent before assigning a BCS classification, to avoid misjudgment in various settings, e.g., drug discovery, formulation design, drug development and regulation.

However, no work has been conducted to compare the China shale plays with other mature shale plays in the North America using multiple experimental methods based on the mineralogy analysis and organic geochemistry.

This should involve an integrated approach of multiple experimental methods to gain confidence in the observed effect.

For 22 of the subsets, the proportion of co-PPIs vis-à-vis the parent reference set was increased; the exceptions were multiple database evidence in fly, and for multiple experimental methods in mouse.

Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades.

discovery using multiple experimental detection methods.

The OmpL36, OmpL37, OmpL47 and OmpL54 proteins met our transmembrane OMP prediction criteria and were further characterized for surface exposure and membrane affinity using multiple complementary experimental methods.

Conserved protein-protein interactions – or interologues – found in multiple organisms, as well as PPIs replicated by multiple studies or distinct experimental methods, carry a higher confidence value and are more likely to represent true interactions [76] [77].

New bioinformatics approaches become even more powerful with the incorporation of cell biology data, and systems biology offers ways to integrate computational and experimental methods at multiple scales from biochemistry through to individual levels.

In order to identify differentially expressed genes among various RNA-seq datasets obtained from different experimental designs, an appropriate normalization method for calibrating multiple experimental datasets is the first challenging problem.