Towards sound epistemological foundations of statistical methods for high-dimensional biology. - Wikidata - awgldk - TriplyDB

Towards sound epistemological foundations of statistical methods for high-dimensional biology.

Towards sound epistemological foundations of statistical methods for high-dimensional biology.

http://www.wikidata.org/entity/Q42634755

about

On the impoverishment of scientific education On the epistemological crisis in genomics Robust detection of periodic time series measured from biological systems.The PowerAtlas: a power and sample size atlas for microarray experimental design and research.Evaluation of methods for oligonucleotide array data via quantitative real-time PCR Assessing Dissimilarity Measures for Sample-Based Hierarchical Clustering of RNA Sequencing Data Using Plasmode Datasets Inferential considerations for low-count RNA-seq transcripts: a case study on the dominant prairie grass Andropogon gerardii.Variation in fiberoptic bead-based oligonucleotide microarrays: dispersion characteristics among hybridization and biological replicate samples.Predicting cancer involvement of genes from heterogeneous data.Proteomic analysis of amniotic fluid to identify women with preterm labor and intra-amniotic inflammation/infection: the use of a novel computational method to analyze mass spectrometric profiling The Beta-Binomial Distribution for Estimating the Number of False Rejections in Microarray Gene Expression Studies.Multiple-rule bias in the comparison of classification rules Industrial methodology for process verification in research (IMPROVER): toward systems biology verification Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery.Evaluating statistical analysis models for RNA sequencing experiments.Coverage recommendations for methylation analysis by whole-genome bisulfite sequencing Empirical evaluation of data transformations and ranking statistics for microarray analysis.Forward-time simulation of realistic samples for genome-wide association studies Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.Evaluation of microarray data normalization procedures using spike-in experiments Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data.Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis.Evaluating statistical methods using plasmode data sets in the age of massive public databases: an illustration using false discovery rates.Reproducible clusters from microarray research: whither?Microarray data analysis: from disarray to consolidation and consensus.Predicting survival within the lung cancer histopathological hierarchy using a multi-scale genomic model of development Proteomic profiling of amniotic fluid in preterm labor using two-dimensional liquid separation and mass spectrometry.Within-Cluster Resampling for Analysis of Family Data: Ready for Prime-Time?Comparing self-reported ethnicity to genetic background measures in the context of the Multi-Ethnic Study of Atherosclerosis (MESA).Rank-based inverse normal transformations are increasingly used, but are they merited?Real data examples in statistical methods papers: Tremendously valuable, and also tremendously misvalued.A comprehensive and universal method for assessing the performance of differential gene expression analyses.A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data analysis.From Measurement to Analysis Reporting: Grand Challenges in Nutritional Methodology.The illusion of distribution-free small-sample classification in genomics.The search for genenotype/phenotype associations and the phenome scan.Challenges and approaches to statistical design and inference in high-dimensional investigations.Analysis of microarray experiments of gene expression profiling.Validation of computational methods in genomics.The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies

P2860

Q24288942-0731E458-B723-4E78-BCF8-447F99F38EFB Q24652735-6F910136-1B5C-456B-B144-570FBEA5F3C1 Q24815042-FB0D7025-0EA1-41E3-9C08-2B244A9D0BC3 Q25255599-3B48C5FE-564E-4DD7-82D7-169D04FA7BAB Q25257085-1F25813D-00D7-473D-BD7E-8963FC406E96 Q27302976-5862E6D5-BBF3-43AE-B4D5-00E8C6DFB240 Q27316733-BECE7F9F-1DCD-461F-A443-C497DD04C82F Q30477759-D4EF858E-C6CA-4BF5-BDD1-F6CFF3157E7F Q30481763-A93D3531-B227-4D26-86CF-E1641A956EB4 Q30484179-EEE8B3D8-886F-4AA8-A86D-2735D7E15FB3 Q30493875-1DD7065D-23BA-464B-9D10-055C9E2496CD Q30500802-F754276F-0410-406A-B7E4-E3F82C23275A Q30513851-86C5E295-743C-4132-B8B6-2F5F5A2724D1 Q30524877-D7A05A54-D862-40A3-A600-FAD56F0354FF Q30544922-7A56FD01-445A-4867-8A87-86E6A24D49E0 Q30622907-F15FE988-9944-4C4B-AE06-46BFAB38F6A9 Q30969691-3E98BFBE-453B-4609-86D0-4533EBD0068F Q30988891-F9DA7B93-6DBA-4E8A-BE61-4657EE694D96 Q30994965-9B8896B3-8AB1-42DE-9765-172AE17DC51D Q31044243-44406D84-076F-4CAB-AC4F-DFD435CA2B87 Q31115839-EA1E3C18-6981-4894-A665-1A2F02FE6656 Q31136755-6EBAE953-CC14-4B88-A350-48EEE3335FB2 Q31159887-54D9377C-15EF-498B-A789-B78624A3C8F3 Q33219773-B7ADD71C-37EA-4268-8394-D0E4BEAC93BA Q33230059-B9FA26B1-4CB0-4E88-8F7E-5F08AB86E4E0 Q33247966-0DFF4FE2-8B70-4F6E-A6BB-C48D9EEA4251 Q33384672-FDE16DA6-A4B1-4B3F-97CB-9DB0889AE19B Q33642800-B02191F0-B1AD-44FC-9AFB-E634C505BF2E Q33837422-55C35353-69C6-4B90-890D-3415D4C9C265 Q34066450-8A01686E-27AF-493B-985B-75A8C4FB1C3B Q34088241-AABFBC94-A374-4563-9CB0-B0933A353F5C Q34115329-E1BE3B21-51B2-499A-BDC6-2FB55B7ABDCD Q34569794-63C7669B-5D89-4220-A6C4-D5EB896CAA6F Q34915827-9131A12C-E757-495D-8ED7-CE9CBCED5777 Q35132744-7AF761B1-CF6B-4F32-86FB-792A31053C56 Q36164141-0E64A456-B874-4E9F-8F0E-2E0E2882E5D2 Q36342302-50B7C882-BA2F-4816-A6D7-3CB68C56F353 Q36731621-80FA0C3C-3607-4E15-BFBC-866B5B667E32 Q36775869-B9D8C9C9-3EA1-470F-9F4D-32A49C3B18C2 Q37183386-95B66FD1-A18C-4E20-84F4-02B5DB6EB69C

P2860

Towards sound epistemological foundations of statistical methods for high-dimensional biology.

http://www.wikidata.org/entity/Q42634755

description

2004 nî lūn-bûn

@nan

2004年の論文

@ja

2004年論文

@yue

2004年論文

@zh-hant

2004年論文

@zh-hk

2004年論文

@zh-mo

2004年論文

@zh-tw

2004年论文

@wuu

2004年论文

@zh

2004年论文

@zh-cn

name

Towards sound epistemological ...... for high-dimensional biology.

@en

Towards sound epistemological ...... for high-dimensional biology.

@nl

type

label

Towards sound epistemological ...... for high-dimensional biology.

@en

Towards sound epistemological ...... for high-dimensional biology.

@nl

prefLabel

Towards sound epistemological ...... for high-dimensional biology.

@en

Towards sound epistemological ...... for high-dimensional biology.

@nl

P1433

Q42634755-DF8E0813-D8E9-4943-B6AB-17E0CA3F67FF

P1476

Q42634755-BE9AAEB1-4F1C-438B-B8D0-997004632FF1

P2093

Q42634755-02E5EA9A-8A40-4F25-8440-25538DCF477A

Q42634755-508A17DA-5AF3-4424-9E25-8EE35FE00C40

P2860

Q42634755-08FD32F0-2881-4085-89BA-11170E4FC8F0

Q42634755-1074B3C3-5CF5-45AA-8BC9-54AA99377B31

Q42634755-10EC77C8-D7CF-40DA-840F-76E97AB48D8C

Q42634755-1CEE9AAE-A9B1-4E94-8BED-CBF2004FA8B1

Q42634755-1DFAB35A-D0C4-408A-913E-C767C6FAAA6B

Q42634755-2055ECDA-8B57-4596-8488-154B51AF0CF7

Q42634755-21ABB3D8-C2A8-44B8-9413-49FAE915ED5D

Q42634755-28B49677-F34D-4C24-83AD-D15D2FDBB1E9

Q42634755-2AA1DB08-7D2A-43DF-BCEE-12CD5C08D4A7

Q42634755-2CC9BFBA-C3D2-47A5-87BB-BC0BE170B1D2

P2888

Q42634755-7E1152F6-A89A-47C9-82B1-077DCCE74563

P304

Q42634755-EAA7F4F0-B8B4-43D3-B86C-2AFAA565937D

P31

Q42634755-421D18E1-3018-4530-BDB4-42F3CD0EADB6

P356

Q42634755-D04AB753-0B9E-4376-82BF-A0A00916692C

P407

Q42634755-B915F9A7-1ACB-4124-939F-0A34C457503E

P433

Q42634755-DB9A2470-061B-44A6-AD77-520ED4997268

P478

Q42634755-95A3FF99-A4C4-46BE-925C-FED772295644

P50

Q42634755-6B872C68-B109-4ABD-AF0E-8267717C1274

P577

Q42634755-506CA1BD-8E7E-4A2A-AC98-FAEB917B3DDB

P5875

Q42634755-F57F97FC-F474-4AEC-BEF2-D024E8623801

P6179

Q42634755-27CB1385-867A-4C51-8095-FFDF43572F78

P698

Q42634755-A4D4F130-DFFD-4A63-8175-6B4E794262B8

P921

Q42634755-EF27577F-5F28-4228-900A-3FE13F183FEB

P356

P1433

Nature Genetics

P1476

Towards sound epistemological ...... for high-dimensional biology.

@en

P2093

Murat Tanik

http://www.w3.org/2001/XMLSchema#string

Tapan Mehta

http://www.w3.org/2001/XMLSchema#string

P2860

Significance analysis of microarrays applied to the ionizing radiation response

Cluster stability scores for microarray data in cancer studies.

Minimum information about a microarray experiment (MIAME)-toward standards for microarray data

Summaries of Affymetrix GeneChip probe level data

Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results

Identifying differentially expressed genes using false discovery rate controlling procedures

Assessing gene significance from cDNA microarray expression data via mixed models

A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes

Tests for gaussian repeated measures with missing data in small samples.

Selection bias in gene extraction on the basis of microarray gene-expression data.

P2888

P304

943-947

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1038/NG1422

http://www.w3.org/2001/XMLSchema#string

P407

P433

9

http://www.w3.org/2001/XMLSchema#string

P478

36

http://www.w3.org/2001/XMLSchema#string

P50

David B. Allison

P577

2004-09-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

8372982

http://www.w3.org/2001/XMLSchema#string

P6179

1027115586

http://www.w3.org/2001/XMLSchema#string

P698

15340433

http://www.w3.org/2001/XMLSchema#string

P921