روش‌های محاسباتی برای پیش‌بینی سایت‌های اصلاح پس از ترجمه Computational Methods for Predicting Post-Translational Modification Sites

فهرست مطالب: Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv 1 Maximizing Depth of PTM Coverage: Generating Robust MS Datasets for Computational Prediction Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Anthony A. Iannetta and Leslie M. Hicks 2 PLDMS: Phosphopeptide Library Dephosphorylation Followed by Mass Spectrometry Analysis to Determine the Specificity of Phosphatases for Dephosphorylation Site Sequences . . . . . . . . . . . . . . . . . . . . . . . . 43 Thomas Kokot, Bernhard Hoermann, Dominic Helm, Jeremy E. Chojnacki, Mikhail M. Savitski, and Maja Ko ¨hn 3 FEPS: A Tool for Feature Extraction from Protein Sequence . . . . . . . . . . . . . . . . . 65 Hamid Ismail, Clarence White, Hussam AL-Barakati, Robert H. Newman, and Dukka B. KC 4 A Pretrained ELECTRA Model for Kinase-Specific Phosphorylation Site Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Lei Jiang, Duolin Wang, and Dong Xu 5 iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Iman Dehzangi, Alok Sharma, and Swakkhar Shatabda 6 Functions of Glycosylation and Related Web Resources for Its Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Kiyoko F. Aoki-Kinoshita 7 Analysis of Posttranslational Modifications in Arabidopsis Proteins and Metabolic Pathways Using the FAT-PTM Database . . . . . . . . . . . . . 145 Madison N. Blea and Ian S. Wallace 8 Bioinformatic Analyses of Peroxiredoxins and RF-Prx: A Random Forest-Based Predictor and Classifier for Prxs . . . . . . . . . . . . . . . . . . . . 155 Hussam AL-Barakati, Robert H. Newman, Dukka B. KC, and Leslie B. Poole 9 Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Ghazaleh Taherzadeh, Matthew Campbell, and Yaoqi Zhou 10 iPTMnet RESTful API for Post-translational Modification Network Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Sachin Gavali, Karen E. Ross, Julie Cowart, Chuming Chen, and Cathy H. Wu xiii11 Systematic Characterization of Lysine Post-translational Modification Sites Using MUscADEL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Zhen Chen, Xuhan Liu, Fuyi Li, Chen Li, Tatiana Marquez-Lago Andre´ Leier, Geoffrey I. Webb, Dakang Xu, Tatsuya Akutsu, and Jiangning Song 12 Enhancing the Discovery of Functional Post-Translational Modification Sites with Machine Learning Models – Development, Validation, and Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Nolan English and Matthew Torres 13 Exploration of Protein Posttranslational Modification Landscape and Cross Talk with CrossTalkMapper. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 Arthur Grimaud, Frederik Haugaard Holck, Louise Marie Buur, Rebecca Kirsch, and Veit Schwammle € 14 PTM-X: Prediction of Post-Translational Modification Crosstalk Within and Across Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Yuxuan Li, Yuanhua Huang, and Tingting Li 15 Deep Learning–Based Advances In Protein Posttranslational Modification Site and Protein Cleavage Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Subash C. Pakhrin, Suresh Pokharel, Hiroto Saigo, and Dukka B. KC Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323    مشخصات فایل
عنوان (Title):	Computational Methods for Predicting Post-Translational Modification Sites
نام فایل (File name):	918-www.GeneProtocols.ir-Computational Methods for Predicting Post-Translational Modification Sites-Humana (2022).pdf
عنوان فارسی (Title in Persian):	روش‌های محاسباتی برای پیش‌بینی سایت‌های اصلاح پس از ترجمه
ایجاد کننده:	Dukka B. KC
زبان (Language):	انگلیسی English
سال انتشار:	2022
شابک ISBN:	1071623168, 9781071623169
نوع سند (Doc. type):	کتاب
فرمت (File extention):	PDF
حجم فایل (File size):	9.52 مگابایت
تعداد صفحات (Book length in pages):	337

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