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For: Morello G, Salomone S, D'Agata V, Conforti FL, Cavallaro S. From Multi-Omics Approaches to Precision Medicine in Amyotrophic Lateral Sclerosis. Front Neurosci 2020;14:577755. [PMID: 33192262 DOI: 10.3389/fnins.2020.577755] [Cited by in Crossref: 21] [Cited by in F6Publishing: 23] [Article Influence: 10.5] [Reference Citation Analysis]
Number Citing Articles
1 Swaroop RS, Pradhan SS, Darshan VMD, Phalguna KS, Sivaramakrishnan V. Integrated network pharmacology approach shows a potential role of Ginseng catechins and ginsenosides in modulating protein aggregation in Amyotrophic Lateral Sclerosis. 3 Biotech 2022;12:333. [DOI: 10.1007/s13205-022-03401-1] [Reference Citation Analysis]
2 Das T, Kaur H, Gour P, Prasad K, Lynn AM, Prakash A, Kumar V. Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review. Briefings in Bioinformatics 2022;23. [DOI: 10.1093/bib/bbac442] [Reference Citation Analysis]
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5 Mukherjee A, Ghosh S, Biswas D, Rao A, Shetty P, Epari S, Moiyadi A, Srivastava S. Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples. OMICS: A Journal of Integrative Biology 2022;26:512-520. [DOI: 10.1089/omi.2022.0082] [Reference Citation Analysis]
6 Sai Swaroop R, Akhil PS, Sai Sanwid P, Bandana P, Raksha RK, Meghana M, Bibha C, Sivaramakrishnan V. Integrated multi-omic data analysis and validation with yeast model show oxidative phosphorylation modulates protein aggregation in amyotrophic lateral sclerosis. J Biomol Struct Dyn 2022;:1-20. [PMID: 35749136 DOI: 10.1080/07391102.2022.2090441] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Ruffo P, Cavallaro S, Conforti FL. The Advent of Omics Sciences in Clinical Trials of Motor Neuron Diseases. JPM 2022;12:758. [DOI: 10.3390/jpm12050758] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Nakaya T. A specific gene-splicing alteration in the SNRNP70 gene as a hallmark of an ALS subtype. Gene 2022;818:146203. [PMID: 35101583 DOI: 10.1016/j.gene.2022.146203] [Reference Citation Analysis]
9 Schumacher-schuh A, Bieger A, Borelli WV, Portley MK, Awad PS, Bandres-ciga S. Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases. Front Neurol 2022;12:792227. [DOI: 10.3389/fneur.2021.792227] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
10 Espinosa-Espinosa J, González-Barriga A, López-Castel A, Artero R. Deciphering the Complex Molecular Pathogenesis of Myotonic Dystrophy Type 1 through Omics Studies. Int J Mol Sci 2022;23:1441. [PMID: 35163365 DOI: 10.3390/ijms23031441] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
11 Pampalakis G, Angelis G, Zingkou E, Vekrellis K, Sotiropoulou G. A chemogenomic approach is required for effective treatment of amyotrophic lateral sclerosis. Clinical & Translational Med 2022;12. [DOI: 10.1002/ctm2.657] [Reference Citation Analysis]
12 Grima N, Henden L, Watson O, Blair IP, Williams KL. Simultaneous Isolation of High-Quality RNA and DNA From Postmortem Human Central Nervous System Tissues for Omics Studies. J Neuropathol Exp Neurol 2021:nlab129. [PMID: 34939123 DOI: 10.1093/jnen/nlab129] [Reference Citation Analysis]
13 Thompson AG, Oeckl P, Feneberg E, Bowser R, Otto M, Fischer R, Kessler B, Turner MR. Advancing mechanistic understanding and biomarker development in amyotrophic lateral sclerosis. Expert Rev Proteomics 2021;18:977-94. [PMID: 34758687 DOI: 10.1080/14789450.2021.2004890] [Reference Citation Analysis]
14 Lamas NJ, Roybon L. Harnessing the Potential of Human Pluripotent Stem Cell-Derived Motor Neurons for Drug Discovery in Amyotrophic Lateral Sclerosis: From the Clinic to the Laboratory and Back to the Patient. Front Drug Discov 2021;1:773424. [DOI: 10.3389/fddsv.2021.773424] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
15 La Cognata V, Golini E, Iemmolo R, Balletta S, Morello G, De Rosa C, Villari A, Marinelli S, Vacca V, Bonaventura G, Dell'Albani P, Aronica E, Mammano F, Mandillo S, Cavallaro S. CXCR2 increases in ALS cortical neurons and its inhibition prevents motor neuron degeneration in vitro and improves neuromuscular function in SOD1G93A mice. Neurobiol Dis 2021;160:105538. [PMID: 34743985 DOI: 10.1016/j.nbd.2021.105538] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
16 Stifani S. Taking Cellular Heterogeneity Into Consideration When Modeling Astrocyte Involvement in Amyotrophic Lateral Sclerosis Using Human Induced Pluripotent Stem Cells. Front Cell Neurosci 2021;15:707861. [PMID: 34602979 DOI: 10.3389/fncel.2021.707861] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
17 Reska D, Czajkowski M, Jurczuk K, Boldak C, Kwedlo W, Bauer W, Koszelew J, Kretowski M. Integration of solutions and services for multi-omics data analysis towards personalized medicine. Biocybernetics and Biomedical Engineering 2021;41:1646-63. [DOI: 10.1016/j.bbe.2021.10.005] [Reference Citation Analysis]
18 Correa Rojo A, Heylen D, Aerts J, Thas O, Hooyberghs J, Ertaylan G, Valkenborg D. Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review. Front Physiol 2021;12:723510. [PMID: 34512391 DOI: 10.3389/fphys.2021.723510] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
19 Buczyńska A, Sidorkiewicz I, Trochimiuk A, Ławicki S, Krętowski AJ, Zbucka-Krętowska M. Novel Approaches to an Integrated Route for Trisomy 21 Evaluation. Biomolecules 2021;11:1328. [PMID: 34572541 DOI: 10.3390/biom11091328] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
20 Picard M, Scott-Boyer MP, Bodein A, Périn O, Droit A. Integration strategies of multi-omics data for machine learning analysis. Comput Struct Biotechnol J 2021;19:3735-46. [PMID: 34285775 DOI: 10.1016/j.csbj.2021.06.030] [Cited by in Crossref: 41] [Cited by in F6Publishing: 49] [Article Influence: 41.0] [Reference Citation Analysis]
21 Boniolo F, Dorigatti E, Ohnmacht AJ, Saur D, Schubert B, Menden MP. Artificial intelligence in early drug discovery enabling precision medicine. Expert Opin Drug Discov 2021;16:991-1007. [PMID: 34075855 DOI: 10.1080/17460441.2021.1918096] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 8.0] [Reference Citation Analysis]
22 Khan AR, Roy R. Metabolic profiling leading to clinical phenomics: From bench to bedside. Epigenetics and Metabolomics 2021. [DOI: 10.1016/b978-0-323-85652-2.00018-x] [Reference Citation Analysis]
23 Borgese N, Navone F, Nukina N, Yamanaka T. Mutant VAPB: Culprit or Innocent Bystander of Amyotrophic Lateral Sclerosis? Contact 2021;4:251525642110225. [DOI: 10.1177/25152564211022515] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
24 Karkossa I, Raps S, von Bergen M, Schubert K. Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages. Int J Mol Sci 2020;21:E9371. [PMID: 33317022 DOI: 10.3390/ijms21249371] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]