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For: Ramesh M, Gopinath P, Govindaraju T. Role of Post-translational Modifications in Alzheimer's Disease. Chembiochem 2020;21:1052-79. [PMID: 31863723 DOI: 10.1002/cbic.201900573] [Cited by in Crossref: 8] [Cited by in F6Publishing: 13] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Liu X, Xu L, Lu Y, Yang T, Gu X, Wang L, Liu Y. Deep_KsuccSite: A novel deep learning method for the identification of lysine succinylation sites. Front Genet 2022;13:1007618. [DOI: 10.3389/fgene.2022.1007618] [Reference Citation Analysis]
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4 Bergasa-Caceres F, Rabitz HA. Protein Folding Interdiction Strategy for Therapeutic Drug Development in Viral Diseases: Ebola VP40 and Influenza A M1. Int J Mol Sci 2022;23:3906. [PMID: 35409264 DOI: 10.3390/ijms23073906] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Horta-López PH, Mendoza-Franco G, Rodríguez-Cruz F, Torres-Cruz FM, Hernández-Echeagaray E, Jarero-Basulto JJ, Rícny J, Garduño BF, Garcia-Sierra F. Association of α-1-Antichymotrypsin Expression with the Development of Conformational Changes of Tau Protein in Alzheimer's Disease Brain. Neuroscience 2022:S0306-4522(22)00002-1. [PMID: 35007692 DOI: 10.1016/j.neuroscience.2022.01.002] [Reference Citation Analysis]
6 Tan MS, Cheah PL, Chin AV, Looi LM, Chang SW. A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach. Comput Biol Med 2021;139:104947. [PMID: 34678481 DOI: 10.1016/j.compbiomed.2021.104947] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
7 Ramesh M, Acharya A, Murugan NA, Ila H, Govindaraju T. Thiophene-Based Dual Modulators of Aβ and Tau Aggregation. Chembiochem 2021. [PMID: 34546619 DOI: 10.1002/cbic.202100383] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Huo MZ, Hu ZL, Ying YL, Long YT. Enhanced identification of Tau acetylation and phosphorylation with an engineered aerolysin nanopore. Proteomics 2021;:e2100041. [PMID: 34545670 DOI: 10.1002/pmic.202100041] [Cited by in Crossref: 1] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
9 Sen MK, Almuslehi MSM, Shortland PJ, Mahns DA, Coorssen JR. Proteomics of Multiple Sclerosis: Inherent Issues in Defining the Pathoetiology and Identifying (Early) Biomarkers. Int J Mol Sci 2021;22:7377. [PMID: 34298997 DOI: 10.3390/ijms22147377] [Cited by in F6Publishing: 6] [Reference Citation Analysis]
10 Khayachi A, Schorova L, Alda M, Rouleau GA, Milnerwood AJ. Posttranslational modifications & lithium's therapeutic effect-Potential biomarkers for clinical responses in psychiatric & neurodegenerative disorders. Neurosci Biobehav Rev 2021;127:424-45. [PMID: 33971223 DOI: 10.1016/j.neubiorev.2021.05.002] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
11 Moorthy H, Govindaraju T. Dendrimer Architectonics to Treat Cancer and Neurodegenerative Diseases with Implications in Theranostics and Personalized Medicine. ACS Appl Bio Mater 2021;4:1115-39. [PMID: 35014470 DOI: 10.1021/acsabm.0c01319] [Cited by in Crossref: 12] [Cited by in F6Publishing: 7] [Article Influence: 12.0] [Reference Citation Analysis]
12 Ji Y, Ren C, Miao H, Pang Z, Xiao R, Yang X, Xuan W. Genetically encoding ε- N -benzoyllysine in proteins. Chem Commun 2021;57:1798-801. [DOI: 10.1039/d0cc07954e] [Cited by in Crossref: 1] [Cited by in F6Publishing: 7] [Article Influence: 1.0] [Reference Citation Analysis]
13 Meng F, Liang Z, Zhao K, Luo C. Drug design targeting active posttranslational modification protein isoforms. Med Res Rev 2021;41:1701-50. [PMID: 33355944 DOI: 10.1002/med.21774] [Cited by in Crossref: 1] [Cited by in F6Publishing: 9] [Article Influence: 0.5] [Reference Citation Analysis]
14 Datta LP, Samanta S, Govindaraju T. Polyampholyte-Based Synthetic Chaperone Modulate Amyloid Aggregation and Lithium Delivery. ACS Chem Neurosci 2020;11:2812-26. [PMID: 32816457 DOI: 10.1021/acschemneuro.0c00369] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
15 Rangaswamy U, Dharshini SAP, Yesudhas D, Gromiha MM. VEPAD - Predicting the effect of variants associated with Alzheimer's disease using machine learning. Comput Biol Med 2020;124:103933. [PMID: 32828070 DOI: 10.1016/j.compbiomed.2020.103933] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]