207 related articles for article (PubMed ID: 35269707)
1. A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson's Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples.
Termine A; Fabrizio C; Strafella C; Caputo V; Petrosini L; Caltagirone C; Cascella R; Giardina E
Int J Mol Sci; 2022 Feb; 23(5):. PubMed ID: 35269707
[TBL] [Abstract][Full Text] [Related]
2. Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning.
Salmanpour MR; Shamsaei M; Saberi A; Hajianfar G; Soltanian-Zadeh H; Rahmim A
Comput Biol Med; 2021 Feb; 129():104142. PubMed ID: 33260101
[TBL] [Abstract][Full Text] [Related]
3. A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson's disease.
Su L; Wang C; Zheng C; Wei H; Song X
BMC Med Genomics; 2018 Apr; 11(1):40. PubMed ID: 29653596
[TBL] [Abstract][Full Text] [Related]
4. Comparative analysis of RNA-Seq data from brain and blood samples of Parkinson's disease.
Chatterjee P; Roy D
Biochem Biophys Res Commun; 2017 Mar; 484(3):557-564. PubMed ID: 28131841
[TBL] [Abstract][Full Text] [Related]
5. Construction of Parkinson's disease marker-based weighted protein-protein interaction network for prioritization of co-expressed genes.
George G; Valiya Parambath S; Lokappa SB; Varkey J
Gene; 2019 May; 697():67-77. PubMed ID: 30776463
[TBL] [Abstract][Full Text] [Related]
6. Skeletal muscle transcriptional networks linked to type I myofiber grouping in Parkinson's disease.
Lavin KM; Sealfon SC; McDonald MN; Roberts BM; Wilk K; Nair VD; Ge Y; Lakshman Kumar P; Windham ST; Bamman MM
J Appl Physiol (1985); 2020 Feb; 128(2):229-240. PubMed ID: 31829804
[TBL] [Abstract][Full Text] [Related]
7. Long non-coding RNA and alternative splicing modulations in Parkinson's leukocytes identified by RNA sequencing.
Soreq L; Guffanti A; Salomonis N; Simchovitz A; Israel Z; Bergman H; Soreq H
PLoS Comput Biol; 2014 Mar; 10(3):e1003517. PubMed ID: 24651478
[TBL] [Abstract][Full Text] [Related]
8. Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease.
Salmanpour MR; Shamsaei M; Rahmim A
Comput Methods Programs Biomed; 2021 Jul; 206():106131. PubMed ID: 34015757
[TBL] [Abstract][Full Text] [Related]
9. RNA-Seq-Based Breast Cancer Subtypes Classification Using Machine Learning Approaches.
Yu Z; Wang Z; Yu X; Zhang Z
Comput Intell Neurosci; 2020; 2020():4737969. PubMed ID: 33178256
[TBL] [Abstract][Full Text] [Related]
10. A computational approach to identify blood cell-expressed Parkinson's disease biomarkers that are coordinately expressed in brain tissue.
Moni MA; Rana HK; Islam MB; Ahmed MB; Xu H; Hasan MAM; Lei Y; Quinn JMW
Comput Biol Med; 2019 Oct; 113():103385. PubMed ID: 31437626
[TBL] [Abstract][Full Text] [Related]
11. Expanding the search for genetic biomarkers of Parkinson's disease into the living brain.
Benoit SM; Xu H; Schmid S; Alexandrova R; Kaur G; Thiruvahindrapuram B; Pereira SL; Jog M; Hebb MO
Neurobiol Dis; 2020 Jul; 140():104872. PubMed ID: 32302674
[TBL] [Abstract][Full Text] [Related]
12. Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection.
Yoo R; Rychel K; Poudel S; Al-Bulushi T; Yuan Y; Chauhan S; Lamoureux C; Palsson BO; Sastry A
mSphere; 2022 Apr; 7(2):e0003322. PubMed ID: 35306876
[TBL] [Abstract][Full Text] [Related]
13. A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data.
Srinivasan S; Leshchyk A; Johnson NT; Korkin D
RNA; 2020 Oct; 26(10):1303-1319. PubMed ID: 32532794
[TBL] [Abstract][Full Text] [Related]
14. Transcriptomic Profiling of Circular RNA in Different Brain Regions of Parkinson's Disease in a Mouse Model.
Jia E; Zhou Y; Liu Z; Wang L; Ouyang T; Pan M; Bai Y; Ge Q
Int J Mol Sci; 2020 Apr; 21(8):. PubMed ID: 32344560
[TBL] [Abstract][Full Text] [Related]
15. Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.
Xiao B; He N; Wang Q; Cheng Z; Jiao Y; Haacke EM; Yan F; Shi F
Neuroimage Clin; 2019; 24():102070. PubMed ID: 31734535
[TBL] [Abstract][Full Text] [Related]
16. Identifying the hub gene and immune infiltration of Parkinson's disease using bioinformatical methods.
Liu SH; Wang YL; Jiang SM; Wan XJ; Yan JH; Liu CF
Brain Res; 2022 Jun; 1785():147879. PubMed ID: 35278479
[TBL] [Abstract][Full Text] [Related]
17. Gene Prioritization in Parkinson's Disease Using Human Protein-Protein Interaction Network.
Prajapati R; Emerson IA
J Comput Biol; 2020 Nov; 27(11):1610-1621. PubMed ID: 32343917
[TBL] [Abstract][Full Text] [Related]
18. An Integrated Network Analysis of mRNA and Gene Expression Profiles in Parkinson's Disease.
Wang Y; Wang Z
Med Sci Monit; 2020 Mar; 26():e920846. PubMed ID: 32210219
[TBL] [Abstract][Full Text] [Related]
19. Repositioning drugs by targeting network modules: a Parkinson's disease case study.
Yue Z; Arora I; Zhang EY; Laufer V; Bridges SL; Chen JY
BMC Bioinformatics; 2017 Dec; 18(Suppl 14):532. PubMed ID: 29297292
[TBL] [Abstract][Full Text] [Related]
20. Integrative analysis of potential biomarkers and immune cell infiltration in Parkinson's disease.
Chen X; Cao W; Zhuang Y; Chen S; Li X
Brain Res Bull; 2021 Dec; 177():53-63. PubMed ID: 34536521
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
