Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: cran: MXM

https://packages.ecosyste.ms/registries/cran.r-project.org/packages/MXM

Feature Selection (Including Multiple Solutions) and Bayesian Networks
52 versions
Latest release: over 2 years ago
1,372 downloads last month

Papers Mentioning MXM 7

Learning clinical networks from medical records based on information estimates in mixed-type data
Cited by: 8
Author(s): Vincent Cabeli, Louis Verny, Nadir Sella, Guido Uguzzoni, Marc Verny, Hervé Isambert
Software Mentions: 5
Published: over 4 years ago

10.1038/s41598-021-92341-6

MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance
Cited by: 17
Author(s): Nikita Sushentsev, Leonardo Rundo, Oleg Blyuss, Vincent Gnanapragasam, Evis Sala, Tristan Barrett
Software Mentions: 4
Published: over 3 years ago

10.12688/f1000research.16216.2

Feature selection with the R package MXM
Cited by: 9
Author(s): Michail Tsagris, Ioannis Tsamardinos
Software Mentions: 3
Published: about 5 years ago

10.1371/journal.pone.0190100

Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding
Cited by: 9
Author(s): Gustavo Carreón, Carlos Gershenson, Luis A. Pineda
Software Mentions: 2
Published: almost 7 years ago

10.3389/fgene.2020.00027

Identification of the Prognosis-Related lncRNAs and Genes in Gastric Cancer
Cited by: 11
Author(s): Xiaohui Su, Jianjun Zhang, Wei Yang, Yanqing Liu, Yang Liu, Zexing Shan, Wentao Wang
Software Mentions: 1
Published: almost 5 years ago

10.3389/fmicb.2020.531756

Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling
Cited by: 22
Author(s): Hyun‐Seob Song, James C. Stegen, Emily B. Graham, Joon‐Yong Lee, Vanessa Garayburu‐Caruso, William Nelson, Xingyuan Chen, J. David Moulton, T. D. Scheibe
Software Mentions: 1
Published: about 4 years ago

10.1038/s41598-021-94501-0

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets
Cited by: 18
Author(s): Γεώργιος Παπουτσόγλου, Makrina Karaglani, Vincenzo Lagani, Naomi Thomson, Oluf Dimitri Røe, Ioannis Tsamardinos, Εkaterini Chatzaki
Software Mentions: 1
Published: over 3 years ago