Sentence examples for biased preference from inspiring English sources
The first is my (ever-so-slightly biased) preference.
The Paz domain of Dicer is known to have biased preference for different 3' overhang sequences [40], and differential selection of processed siRNAs by the analogous Argonaut 2 Paz domain may occur similarly [41], [42].
Cognitive impairment might interfere with comprehension and processing of information required to complete preference measurement tasks, leading to biased preference values.
The occurrence frequency of AU and GC nucleotides at the synonymous codon third position was not found to be equal and AU biased preference was observed in four fold degenerate codons of MARV genes which indicates the potential influence of natural selection on codon usage patterns of MARV genes.
The G+C content of the other two positions correlate only weakly with the G+C content of the chromosome, but still exhibit biased preference for different bases: a significant overrepresentation of G and underrepresentation of T at the first position and overrepresentation of A and T and underrepresentation of G at the second position.
Stakeholders' lack of knowledge and risk of personally biased preferences may corrupt the evaluation.
Participants may, for example, report biased preferences when completing the conjoint exercise due to a 'dominant preference' for a particular attribute.
"There is almost no attention to the bias for people, specifically that whites are biased in preference for other whites and provide information, opportunity and influence on behalf of people that they think of as like them," said Nancy DiTomaso, professor at Rutgers Business School, author of The American Non-dilemma: Racial Inequality Without Racism and an expert in diversity in labor force.
Without a heavily biased directional preference by cells, the model predicts a very tortuous vascular network.
We do not know if this selection could have potentially biased the preference assessments.
Without a biased directional preference by cells, the model predicts a tortuous vascular network, regardless of the number or degree of activated cells.
