首页|Data on Apoptosis Reported by Cheng-Yan Wu and Colleagues (Accurately identifyin g positive and negative regulation of apoptosis using fusion features and machin e learning methods)
Data on Apoptosis Reported by Cheng-Yan Wu and Colleagues (Accurately identifyin g positive and negative regulation of apoptosis using fusion features and machin e learning methods)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Cellular Physiology - Apoptosis is the subject of a report. According to news originating from Baotou, People’s Republic of China, by NewsRx correspondents, research stated, “Apoptot ic proteins play a crucial role in the apoptosis process, ensuring a balance bet ween cell proliferation and death. Thus, further elucidating the regulatory mech anisms of apoptosis will enhance our understanding of their functions.” Our news journalists obtained a quote from the research, “However, the developme nt of computational methods to accurately identify positive and negative regulat ion of apoptosis remains a significant challenge. This work proposes a machine l earning model based on multi-feature fusion to effectively identify the roles of positive and negative regulation of apoptosis. Initially, we constructed a reli able benchmark dataset containing 200 positive regulation of apoptosis and 241 n egative regulation of apoptosis proteins. Subsequently, we developed a classifie r that combines the support vector machine (SVM) with pseudo composition of k-sp aced amino acid pairs (PseCKSAAP), composition transition distribution (CTD), di peptide deviation from expected mean (DDE), and PSSM-composition to identify the se proteins. Analysis of variance (ANOVA) was employed to select optimized featu res that could yield the maximum prediction performance.”
BaotouPeople’s Republic of ChinaAsiaApoptosisCellular PhysiologyCyborgsEmerging TechnologiesHealth and Med icineMachine Learning
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