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
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—Wallace Stevens (1879–1955)
“A structure becomes architectural, and not sculptural, when its elements no longer have their justification in nature.”
—Guillaume Apollinaire (1880–1918)
“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)