Titlebook: Computational Methods for Predicting Post-Translational Modification Sites; Dukka B. KC Book 2022 The Editor(s) (if applicable) and The Au

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adduction

Submersible Technology: Adapting to Changed the development of a plethora of deep learning (DL)-based approaches. In this book chapter, we first review some recent DL-based approaches in the field of PTM site prediction. In addition, we also review the recent advances in the not-so-studied PTM, that is, proteolytic cleavage predictions. We

beta-cells

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秘密會(huì)議

FEPS: A Tool for Feature Extraction from Protein Sequence,to extract features from protein sequence/structure often becomes one of the crucial steps for the development of machine learning-based approaches. Over the years, various sequence, structural, and physicochemical descriptors have been developed for proteins and these descriptors have been used to

Ventilator

iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features,PTMs has been identified. Among them, glycation is considered as one of the most important PTMs. Glycation is associated with different neurological disorders including Parkinson and Alzheimer. It is also shown to be responsible for different diseases, including vascular complications of diabetes me

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gospel

Analysis of Posttranslational Modifications in Arabidopsis Proteins and Metabolic Pathways Using thdevelopments in mass spectrometry technology and sample enrichment approaches have led to a massive expansion in the number of identified PTM types and sites within eukaryotic proteins. As these types of data become increasingly available, it is important to develop additional analysis tools and dat