Projects: cran: plsgenomics
https://packages.ecosyste.ms/registries/cran.r-project.org/packages/plsgenomics
PLS Analyses for Genomics
15 versions
Latest release: almost 7 years ago
4 dependent packages
403 downloads last month
Science Score: 85/100
Starting Score: 100 points
Bonuses:
Penalties:
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-15
No science keywords
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Very Likely Science (85)
Papers Mentioning plsgenomics 8
10.1186/1471-2105-9-439
CMA – a comprehensive Bioconductor package for supervised classification with high dimensional dataCited by: 90
Author(s): Martin Slawski, Martin Däumer, Anne‐Laure Boulesteix
Software Mentions: 16
Published: almost 17 years ago
10.1186/s12859-015-0719-5
mAPKL: R/ Bioconductor package for detecting gene exemplars and revealing their characteristicsCited by: 3
Author(s): Αλέξανδρος Σακελλαρίου, George M. Spyrou
Software Mentions: 15
Published: almost 10 years ago
10.6026/97320630013327
Robust Feature Selection Approach for Patient Classification using Gene Expression DataCited by: 6
Author(s): Shahjaman, Nishith Kumar, Shakil Ahmed, AnjumanAra Begum, S. M. Shahinul Islam, Md. Nurul Haque Mollah
Software Mentions: 5
Published: over 7 years ago
10.3389/fgene.2018.00194
Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular PatternsCited by: 3
Author(s): Jinyu Chen, Shihua Zhang
Software Mentions: 5
Published: about 7 years ago
10.1186/1753-6561-5-S9-S19
Gene-based partial least-squares approaches for detecting rare variant associations with complex traitsCited by: 8
Author(s): Asuman Türkmen, Shili Lin
Software Mentions: 4
Published: over 13 years ago
10.1186/1753-6561-8-S1-S58
Identifying rare variant associations in population-based and family-based designsCited by: 2
Author(s): Asuman Türkmen, Shili Lin
Software Mentions: 2
Published: about 11 years ago
10.1371/journal.pone.0164513
Evaluating Transcription Factor Activity Changes by Scoring Unexplained Target Genes in Expression DataCited by: 6
Author(s): Evi Berchtold, Gergely Csaba, Ralf Zimmer
Software Mentions: 1
Published: almost 9 years ago
10.1038/s41598-019-55339-9
Monitoring type 2 diabetes from volatile faecal metabolome in Cushing’s syndrome and single Afmid mouse models via a longitudinal studyCited by: 13
Author(s): Célia Lourenço, Darren J. Kelly, Jack Cantillon, Michael Cauchi, Michele Yon, Liz Bentley, Roger D. Cox, Claire Turner
Software Mentions: 1
Published: over 5 years ago