User profiles for Kim-Anh Lê Cao
Kim-Anh Lê CaoUniversity of Melbourne Verified email at unimelb.edu.au Cited by 11964 |
Multivariate analysis of multiple datasets: a practical guide for chemical ecology
Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites
detectable in a biological sample. Consequently, chemical ecologists are often challenged …
detectable in a biological sample. Consequently, chemical ecologists are often challenged …
Statistical challenges in longitudinal microbiome data analysis
The microbiome is a complex and dynamic community of microorganisms that co-exist
interdependently within an ecosystem, and interact with its host or environment. Longitudinal …
interdependently within an ecosystem, and interact with its host or environment. Longitudinal …
DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays
… Kim-Anh Lê Cao Kim-Anh Lê Cao … Amrit Singh, Casey P Shannon, Benoît Gautier, Florian
Rohart, Michaël Vacher, Scott J Tebbutt, Kim-Anh Lê Cao, DIABLO: an integrative approach for …
Rohart, Michaël Vacher, Scott J Tebbutt, Kim-Anh Lê Cao, DIABLO: an integrative approach for …
[HTML][HTML] mixOmics: An R package for 'omics feature selection and multiple data integration
The advent of high throughput technologies has led to a wealth of publicly available ‘omics
data coming from different sources, such as transcriptomics, proteomics, metabolomics. …
data coming from different sources, such as transcriptomics, proteomics, metabolomics. …
[HTML][HTML] Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems
Background Variable selection on high throughput biological data, such as gene expression
or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant …
or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant …
A sparse PLS for variable selection when integrating omics data
KA Lê Cao, D Rossouw, C Robert-Granié… - … applications in genetics …, 2008 - degruyter.com
Recent biotechnology advances allow for multiple types of omics data, such as transcriptomic,
proteomic or metabolomic data sets to be integrated. The problem of feature selection has …
proteomic or metabolomic data sets to be integrated. The problem of feature selection has …
integrOmics: an R package to unravel relationships between two omics datasets
KA Lê Cao, I González, S Déjean - Bioinformatics, 2009 - academic.oup.com
Motivation: With the availability of many ‘omics’ data, such as transcriptomics, proteomics or
metabolomics, the integrative or joint analysis of multiple datasets from different technology …
metabolomics, the integrative or joint analysis of multiple datasets from different technology …
Citrullinated peptide dendritic cell immunotherapy in HLA risk genotype–positive rheumatoid arthritis patients
In animals, immunomodulatory dendritic cells (DCs) exposed to autoantigen can suppress
experimental arthritis in an antigen-specific manner. In rheumatoid arthritis (RA), disease-…
experimental arthritis in an antigen-specific manner. In rheumatoid arthritis (RA), disease-…
[HTML][HTML] Sparse canonical methods for biological data integration: application to a cross-platform study
Background In the context of systems biology, few sparse approaches have been proposed
so far to integrate several data sets. It is however an important and fundamental issue that …
so far to integrate several data sets. It is however an important and fundamental issue that …
Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments
Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in
recent years, leading to an explosion in the number of tailored data analysis methods. …
recent years, leading to an explosion in the number of tailored data analysis methods. …