201 related articles for article (PubMed ID: 26300978)
1. Principal component gene set enrichment (PCGSE).
Frost HR; Li Z; Moore JH
BioData Min; 2015; 8():25. PubMed ID: 26300978
[TBL] [Abstract][Full Text] [Related]
2. Spectral gene set enrichment (SGSE).
Frost HR; Li Z; Moore JH
BMC Bioinformatics; 2015 Mar; 16():70. PubMed ID: 25879888
[TBL] [Abstract][Full Text] [Related]
3. Unsupervised gene set testing based on random matrix theory.
Frost HR; Amos CI
BMC Bioinformatics; 2016 Nov; 17(1):442. PubMed ID: 27809777
[TBL] [Abstract][Full Text] [Related]
4. Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components.
Wang M; Kornblau SM; Coombes KR
Cancer Inform; 2018; 17():1176935118771082. PubMed ID: 29881252
[TBL] [Abstract][Full Text] [Related]
5. An Independent Filter for Gene Set Testing Based on Spectral Enrichment.
Frost HR; Li Z; Asselbergs FW; Moore JH
IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(5):1076-86. PubMed ID: 26451820
[TBL] [Abstract][Full Text] [Related]
6. Supervised principal component analysis for gene set enrichment of microarray data with continuous or survival outcomes.
Chen X; Wang L; Smith JD; Zhang B
Bioinformatics; 2008 Nov; 24(21):2474-81. PubMed ID: 18753155
[TBL] [Abstract][Full Text] [Related]
7. Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data.
Sill M; Saadati M; Benner A
Bioinformatics; 2015 Aug; 31(16):2683-90. PubMed ID: 25861969
[TBL] [Abstract][Full Text] [Related]
8. A COMPARISON OF PRINCIPAL COMPONENT METHODS BETWEEN MULTIPLE PHENOTYPE REGRESSION AND MULTIPLE SNP REGRESSION IN GENETIC ASSOCIATION STUDIES.
Liu Z; Barnett I; Lin X
Ann Appl Stat; 2020 Mar; 14(1):433-451. PubMed ID: 37398898
[TBL] [Abstract][Full Text] [Related]
9. Patient phenotypes associated with outcome following surgery for mild degenerative cervical myelopathy: a principal component regression analysis.
Badhiwala JH; Witiw CD; Nassiri F; Jaja BNR; Akbar MA; Mansouri A; Merali Z; Ibrahim GM; Wilson JR; Fehlings MG
Spine J; 2018 Dec; 18(12):2220-2231. PubMed ID: 29746963
[TBL] [Abstract][Full Text] [Related]
10. Strategies for reducing large fMRI data sets for independent component analysis.
Wang Z; Wang J; Calhoun V; Rao H; Detre JA; Childress AR
Magn Reson Imaging; 2006 Jun; 24(5):591-6. PubMed ID: 16735180
[TBL] [Abstract][Full Text] [Related]
11. Estimating the number of components and detecting outliers using Angle Distribution of Loading Subspaces (ADLS) in PCA analysis.
Liu YJ; Tran T; Postma G; Buydens LMC; Jansen J
Anal Chim Acta; 2018 Aug; 1020():17-29. PubMed ID: 29655425
[TBL] [Abstract][Full Text] [Related]
12. A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies.
Liu Z; Lin X
J Am Stat Assoc; 2019; 114(527):975-990. PubMed ID: 31564761
[TBL] [Abstract][Full Text] [Related]
13. Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method.
Foley JW; Katagiri F
BMC Bioinformatics; 2008 Nov; 9():508. PubMed ID: 19040754
[TBL] [Abstract][Full Text] [Related]
14. Use of principal component analysis to evaluate the partial organ tolerance of normal tissues to radiation.
Dawson LA; Biersack M; Lockwood G; Eisbruch A; Lawrence TS; Ten Haken RK
Int J Radiat Oncol Biol Phys; 2005 Jul; 62(3):829-37. PubMed ID: 15936567
[TBL] [Abstract][Full Text] [Related]
15. GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.
Wagner F
PLoS One; 2015; 10(11):e0143196. PubMed ID: 26575370
[TBL] [Abstract][Full Text] [Related]
16. Principal component analysis of neuronal ensemble activity reveals multidimensional somatosensory representations.
Chapin JK; Nicolelis MA
J Neurosci Methods; 1999 Dec; 94(1):121-40. PubMed ID: 10638820
[TBL] [Abstract][Full Text] [Related]
17. PCAtest: testing the statistical significance of Principal Component Analysis in R.
Camargo A
PeerJ; 2022; 10():e12967. PubMed ID: 35194531
[TBL] [Abstract][Full Text] [Related]
18. Power Calculation of Multi-step Combined Principal Components with Applications to Genetic Association Studies.
Li Z; Zhang W; Pan D; Li Q
Sci Rep; 2016 May; 6():26243. PubMed ID: 27189724
[TBL] [Abstract][Full Text] [Related]
19. Principal-component-based population structure adjustment in the North American Rheumatoid Arthritis Consortium data: impact of single-nucleotide polymorphism set and analysis method.
Peloso GM; Timofeev N; Lunetta KL
BMC Proc; 2009 Dec; 3 Suppl 7(Suppl 7):S108. PubMed ID: 20017972
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
