@inproceedings{a04625f8107b4eb18683d29a9e074147,
title = "Human fibroblast growth factor 2 hot spot analysis by means of time-frequency transforms",
abstract = "Energy in protein complexes is not uniformly distributed. Some of amino acid residues—called hot spots—contribute most to the total energy of interaction. Hot spots can be determined experimentally or by computational methods. Here we present the application of time-frequency tools such as short-time Fourier transform and S transform to analyze human fibroblast growth factor 2 protein. The timefrequency tools take advantage the Resonant Recognition Model (RRM), which is based on the correlation between spectra of numerical representations of amino acids and their function. Thus, RRM allows for applying digital signal processing tools to amino acid analysis. Methods using time-frequency transforms do not require knowledge of protein structure, thus they help to predict hot spot residues with good accuracy and lower computational requirements comparing to other algorithms.",
keywords = "Fibroblast growth factor, Hot spot, Resonant recognition model, S transform, Short-time Fourier transform",
author = "Anna Tamulewicz and Ewaryst Tkacz",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 5th International Conference on Information Technologies in Biomedicine, ITIB 2016 ; Conference date: 20-06-2016 Through 22-06-2016",
year = "2016",
doi = "10.1007/978-3-319-39904-1\_13",
language = "English",
isbn = "9783319399034",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "147--159",
editor = "Ewa Pi{\c e}tka and Pawel Badura and Jacek Kawa and Wojciech Wieclawek",
booktitle = "Information Technologies in Medicine - 5th International Conference, ITIB 2016, Proceedings",
address = "Germany",
}