MetaFS: performance assessment of biomarker discovery in metaproteomics
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
MetaFS: Performance assessment of biomarker discovery in metaproteomics.
J Tang, M Mou, Y Wang, Y Luo… - Briefings in …, 2021 - search.ebscohost.com
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
MetaFS: Performance assessment of biomarker discovery in metaproteomics.
J Tang, M Mou, Y Wang, Y Luo, F Zhu - Briefings in Bioinformatics, 2021 - europepmc.org
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
MetaFS: Performance assessment of biomarker discovery in metaproteomics
J Tang, M Mou, Y Wang, Y Luo… - Briefings in …, 2021 - academic.oup.com
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
[PDF][PDF] MetaFS: Performance assessment of biomarker discovery in metaproteomics
J Tang, M Mou, Y Wang, Y Luo, F Zhu - 2020 - idrblab.org
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
MetaFS: Performance assessment of biomarker discovery in metaproteomics
J Tang, M Mou, Y Wang, Y Luo… - Briefings in …, 2021 - pubmed.ncbi.nlm.nih.gov
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …
[PDF][PDF] MetaFS: Performance assessment of biomarker discovery in metaproteomics
J Tang, M Mou, Y Wang, Y Luo, F Zhu - Briefings in Bioinformatics, 2021 - idrblab.org
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction
methods can maximally identify the relevant subset of significant differential features and …
methods can maximally identify the relevant subset of significant differential features and …