Secondary structure prediction is a set of techniques in bioinformatics that aim to predict the secondary structures of proteins and nucleic acid sequences based only on knowledge of their primary structure. For proteins, this means predicting the formation of protein structures such as alpha helices and beta strands, while for nucleic acids it means predicting the formation of nucleic acid structures like helixes and stem-loop structures through base pairing and base stacking interactions.
Secondary structure prediction can refer to:
- Protein structure prediction:Secondary structure
- Nucleic acid structure prediction
Famous quotes containing the words secondary, structure and/or prediction:
“Readers are less and less seen as mere non-writers, the subhuman “other” or flawed derivative of the author; the lack of a pen is no longer a shameful mark of secondary status but a positively enabling space, just as within every writer can be seen to lurk, as a repressed but contaminating antithesis, a reader.”
—Terry Eagleton (b. 1943)
“A committee is organic rather than mechanical in its nature: it is not a structure but a plant. It takes root and grows, it flowers, wilts, and dies, scattering the seed from which other committees will bloom in their turn.”
—C. Northcote Parkinson (1909–1993)
“Recent studies that have investigated maternal satisfaction have found this to be a better prediction of mother-child interaction than work status alone. More important for the overall quality of interaction with their children than simply whether the mother works or not, these studies suggest, is how satisfied the mother is with her role as worker or homemaker. Satisfied women are consistently more warm, involved, playful, stimulating and effective with their children than unsatisfied women.”
—Alison Clarke-Stewart (20th century)