LogMiNeR statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool LogMiNeR
info

Tool usage distribution map

This map represents all the scientific publications referring to LogMiNeR per scientific context
info info

Associated diseases

info

Popular tool citations

chevron_left Multi-omic data integration Network visualization chevron_right
Want to access the full stats & trends on this tool?

LogMiNeR specifications

Information


Unique identifier OMICS_23336
Name LogMiNeR
Alternative name Logistic Multiple Network-constrained Regression
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 0.2
Stability Stable
Maintained Yes

Download


download.png

Versioning


No version available

Documentation


Maintainers


Publication for Logistic Multiple Network-constrained Regression

LogMiNeR citations

 (2)
library_books

Multiple network constrained regressions expand insights into influenza vaccination responses

2017
Bioinformatics
PMCID: 5870750
PMID: 28881994
DOI: 10.1093/bioinformatics/btx260

[…] r knowledge leads to many predictive models that highlight context-specific as well as shared aspects of the underlying biology of vaccination response. Thus, we propose this approach, which we term ‘LogMiNeR’ (Logistic Multiple Network-constrained Regression), as a new framework for systems immunology studies. In contrast with previous methods, LogMiNeR fits multiple models, each using different […]

library_books

Development and validation of a Database Forensic Metamodel (DBFM)

2017
PLoS One
PMCID: 5287479
PMID: 28146585
DOI: 10.1371/journal.pone.0170793

[…] table to the selection of appropriate concepts. Finally, the last recognized criterion is the exclusion of specific concepts related to particular fields, such as Oracle Flashback Transaction; Oracle LogMiner; Oracle tools; SQLedit; MySQL utilities; and so on.Therefore, in accordance with the findings of previous studies [–], and [], the authors manually extracted concepts from each model (contain […]


Want to access the full list of citations?
LogMiNeR institution(s)
Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Departments of Pathology and Immunobiology, Yale School of Medicine, New Haven, CT, USA
LogMiNeR funding source(s)
Supported by the National Institutes of Health [grant number U19AI089992]; by K24 AG042489; and by the National Science Foundation Graduate Research Fellowship Program [grant number DGE-1122492].

LogMiNeR reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review LogMiNeR