標(biāo)題: Titlebook: Computational Methods for Predicting Post-Translational Modification Sites; Dukka B. KC Book 2022 The Editor(s) (if applicable) and The Au [打印本頁] 作者: 惡化 時(shí)間: 2025-3-21 19:14
書目名稱Computational Methods for Predicting Post-Translational Modification Sites影響因子(影響力)
書目名稱Computational Methods for Predicting Post-Translational Modification Sites影響因子(影響力)學(xué)科排名
書目名稱Computational Methods for Predicting Post-Translational Modification Sites網(wǎng)絡(luò)公開度
書目名稱Computational Methods for Predicting Post-Translational Modification Sites網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computational Methods for Predicting Post-Translational Modification Sites被引頻次
書目名稱Computational Methods for Predicting Post-Translational Modification Sites被引頻次學(xué)科排名
書目名稱Computational Methods for Predicting Post-Translational Modification Sites年度引用
書目名稱Computational Methods for Predicting Post-Translational Modification Sites年度引用學(xué)科排名
書目名稱Computational Methods for Predicting Post-Translational Modification Sites讀者反饋
書目名稱Computational Methods for Predicting Post-Translational Modification Sites讀者反饋學(xué)科排名
作者: EXUDE 時(shí)間: 2025-3-21 21:59 作者: 寬敞 時(shí)間: 2025-3-22 03:39
Submersible Technology: Adapting to Changenciple behind the SAPH-ire model, how it is developed, how we evaluate its performance, and important caveats to consider when building and interpreting such models. Finally, we discus current limitations of functional PTM prediction models and highlight potential mechanisms for their improvement.作者: entreat 時(shí)間: 2025-3-22 07:13
Functions of Glycosylation and Related Web Resources for Its Prediction,glycan-related databases and a glycan repository, bioinformatics approaches have attempted to predict the glycosylation pathway and the glycosylation sites on proteins. This chapter introduces these methods and related Web resources for understanding glycan function.作者: 割讓 時(shí)間: 2025-3-22 09:41 作者: FIR 時(shí)間: 2025-3-22 16:38 作者: FIR 時(shí)間: 2025-3-22 19:49
Book 2022art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful?.Methods in Molecular Biology?.series, each chapter include作者: Pelvic-Floor 時(shí)間: 2025-3-22 23:09
J. R. McFarlane,M. Mullin,E. Jacksonsed proteomics technologies to maximize PTM coverage are reviewed. Further, requisite experimental validation approaches for PTM predictions are explored to ensure that follow-up mechanistic studies are focused on accurate modification sites.作者: Polydipsia 時(shí)間: 2025-3-23 01:57 作者: aesthetician 時(shí)間: 2025-3-23 07:56 作者: 難解 時(shí)間: 2025-3-23 10:17 作者: ANTH 時(shí)間: 2025-3-23 14:10 作者: 思想靈活 時(shí)間: 2025-3-23 18:49
iPTMnet RESTful API for Post-translational Modification Network Analysis,h provides a way to streamline the integration of iPTMnet data into an automated data analysis workflow. In the first section, we give an overview of the architecture of the API. In the second section, we describe various function defined by the API and provide detailed examples of using these functions.作者: 無可爭辯 時(shí)間: 2025-3-23 22:12
1064-3745 edicting Post-Translational Modification Sites .aims?to be a?useful?guide for researchers who are interested in the field of PTM site prediction.?.978-1-0716-2319-0978-1-0716-2317-6Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: 大罵 時(shí)間: 2025-3-24 02:38
A Pretrained ELECTRA Model for Kinase-Specific Phosphorylation Site Prediction,作者: Decibel 時(shí)間: 2025-3-24 07:25 作者: 下邊深陷 時(shí)間: 2025-3-24 10:48
PLDMS: Phosphopeptide Library Dephosphorylation Followed by Mass Spectrometry Analysis to Determinef protein phosphatases. The approach, termed “phosphopeptide library dephosphorylation followed by mass spectrometry” (PLDMS), allows for the exact control of phosphorylation site incorporation and the synthetic route is capable of covering several thousand peptides in a single tube reaction. Furthe作者: 莎草 時(shí)間: 2025-3-24 16:41 作者: palliate 時(shí)間: 2025-3-24 20:41
iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features,ular benchmarks used for this task. Our results demonstrate that iProtGly-SS is able to achieve 81.61%, 93.62%, and 92.95% prediction accuracies on these benchmarks, which are significantly better than those results reported in the previous studies. iProtGly-SS is implemented as a web-based tool whi作者: 好色 時(shí)間: 2025-3-25 00:21 作者: 明智的人 時(shí)間: 2025-3-25 05:18
Bioinformatic Analyses of Peroxiredoxins and RF-Prx: A Random Forest-Based Predictor and Classifiernamed “RF-Prx” based on a random forest (RF) approach integrated with K-space amino acid pairs (KSAAP) to identify peroxiredoxins and classify them into one of six subgroups. Our process performed in a superior manner compared to other machine learning classifiers. Thus the RF approach integrated wi作者: Ancillary 時(shí)間: 2025-3-25 11:31 作者: 有毛就脫毛 時(shí)間: 2025-3-25 11:49
Systematic Characterization of Lysine Post-translational Modification Sites Using MUscADEL,te Deep Learner for lysine PTMs). Specifically, MUscADEL employs bidirectional long short-term memory (BiLSTM) recurrent neural networks and is capable of predicting eight major types of lysine PTMs in both the human and mouse proteomes. The web server of MUscADEL is publicly available at . for the 作者: Mercantile 時(shí)間: 2025-3-25 16:30
Exploration of Protein Posttranslational Modification Landscape and Cross Talk with CrossTalkMappere present a workflow to visualize histone proteins and their myriad of PTMs based on different R visualization modules applied to data from quantitative middle-down experiments. The procedure can be adapted to diverse experimental designs and is applicable to different proteins and PTMs.作者: 背心 時(shí)間: 2025-3-25 22:05 作者: 殺子女者 時(shí)間: 2025-3-26 02:27 作者: Aviary 時(shí)間: 2025-3-26 05:12 作者: Mhc-Molecule 時(shí)間: 2025-3-26 08:29 作者: 乞丐 時(shí)間: 2025-3-26 15:45 作者: 食品室 時(shí)間: 2025-3-26 17:46
J. R. McFarlane,M. Mullin,E. Jacksonnamed “RF-Prx” based on a random forest (RF) approach integrated with K-space amino acid pairs (KSAAP) to identify peroxiredoxins and classify them into one of six subgroups. Our process performed in a superior manner compared to other machine learning classifiers. Thus the RF approach integrated wi作者: Constant 時(shí)間: 2025-3-27 00:21 作者: 慎重 時(shí)間: 2025-3-27 04:14 作者: 思想 時(shí)間: 2025-3-27 09:18 作者: adduction 時(shí)間: 2025-3-27 12:59
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 作者: beta-cells 時(shí)間: 2025-3-27 17:17 作者: Abrade 時(shí)間: 2025-3-27 20:24 作者: 秘密會議 時(shí)間: 2025-3-28 00:14
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 作者: Ventilator 時(shí)間: 2025-3-28 06:05
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作者: ALT 時(shí)間: 2025-3-28 06:45 作者: gospel 時(shí)間: 2025-3-28 11:14
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作者: wreathe 時(shí)間: 2025-3-28 15:24
Bioinformatic Analyses of Peroxiredoxins and RF-Prx: A Random Forest-Based Predictor and Classifierive damage but also regulate intracellular and intercellular signaling processes involving redox-regulated proteins and pathways. Bioinformatic approaches using computational tools that focus on active site-proximal sequence fragments (known as active site signatures) and iterative clustering and se作者: Obstruction 時(shí)間: 2025-3-28 18:45
Computational Prediction of N- and O-Linked Glycosylation Sites for Human and Mouse Proteins,n and annotation of these sites using experimental approaches are challenging and time consuming. Hence, there is a demand to build fast and efficient computational methods to address this problem. Here, we present the SPRINT-Gly framework containing the largest dataset and a prediction model of gly作者: Musculoskeletal 時(shí)間: 2025-3-29 02:15 作者: 配置 時(shí)間: 2025-3-29 04:41 作者: HAIRY 時(shí)間: 2025-3-29 08:36 作者: hegemony 時(shí)間: 2025-3-29 13:38 作者: Lipoprotein 時(shí)間: 2025-3-29 15:49
PTM-X: Prediction of Post-Translational Modification Crosstalk Within and Across Proteins,role in regulating proteins’ localization, degradation, and functions. Different PTMs both within a single protein and across multiple proteins can work together or regulate reciprocally, known as PTM cross talk. However, high-throughput experimental identifications of PTM cross talk are lack due to作者: 特征 時(shí)間: 2025-3-29 22:11 作者: Lymphocyte 時(shí)間: 2025-3-30 03:32
Dukka B. KCIncludes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts作者: nonsensical 時(shí)間: 2025-3-30 05:05 作者: Constant 時(shí)間: 2025-3-30 10:28
https://doi.org/10.1007/978-1-0716-2317-6site prediction; phosphosite prediction; PhosAt; RF-Chlamy; dbPAF作者: explicit 時(shí)間: 2025-3-30 12:47
978-1-0716-2319-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines
