@inproceedings{855de47473d843978029ca4033868c84,
title = "Peak detection, feature extraction and clustering of peptides fragments ions",
abstract = "This work presents a peak detection technique used to detect Proteomics fragments peaks and investigates if shape-based features and clustering can group the peaks such that the clusters are homogeneous, i.e. contain peaks from a single class. We used Continuous Wavelet Transformation (CWT) and two Gaussian Mixture Model (GMM); K=2 and K=15; for peak detection and clustering, respectively. GMM(K=15) performed better than GMM(K=2) with an f1-score of 0.81 and 0.57 for the good class and the bad class, respectively. Additional features and other clustering techniques need to be investigated to improve the homogeneity of the clusters.",
keywords = "Continuous wavelet transformation, Feature extraction, Fragments, Gaussian mixture model, Proeteomics",
author = "Koena Monyai and {Van Zyl}, Terence and Stoyan Stoychev",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 ; Conference date: 19-11-2019 Through 20-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ISCMI47871.2019.9004314",
language = "English",
series = "2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "144--149",
booktitle = "2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019",
address = "United States",
}