Sentence examples for a more reliable dataset from inspiring English sources

In consequence, combining Genevestigator results with EST abundance data gives a more reliable dataset of genes specifically expressed in a certain organ, seeds in our case.

To generate a more reliable dataset of significant expression changes, we supplemented these gene lists with a further one, found by literature search [ 32].

Sites observed to be phosphorylated in more than one high-througput experiment likely are modified in a more constitutive manner, or at least represent a more reliable dataset of phosphoserines.

In addition, confidence scores were assigned for protein identification by mass spectrometry, so we prune Krogan's dataset with the cut-off thresholds (99.6 for LC-MS/MS protein identification, and 3.4 for MALDI-TOF protein identification) used by Hart et al. (2007) and thus yield a more reliable dataset (called 'Krogan-HighConf') from Krogan's raw data.

On the other hand, chemical analyses of the liquid and solid phases in contact (Ohnishi et al. 2017) present a much more reliable dataset because only an assumption of the local equilibrium is necessary without the information on temperature (it is noted that chemical equilibrium is assumed implicitly when melting temperatures are measured directly).

To dispose of a larger and therefore more reliable dataset, we then expanded our analysis to species pertaining to a single genus, Danio.

Our research is also based on a much larger and more reliable dataset than most previous studies.

Only interactions with a combined score value ≥ 770 were considered in this analysis since they are verified as more reliable dataset containing less false negatives and false positives [28].

In this study, we have constructed a more reliable training dataset to build classifiers to determine the aggregation propensity and GroEL dependency in 1132 eubacterial proteomes, based solely on the amino acid sequences.

Performance comparison between microarray and next generation based digital expression profiling suggests that the two methodologies combined may survey the transcriptome in a better way than each on its own, and therefore generate more reliable datasets and uncovering additional new functions.

We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets.