Difference between revisions of "Literature Studies"
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== Results from Literature == | == Results from Literature == | ||
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| + | === Classification === | ||
| + | ===== 2003 ===== | ||
| + | Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data | ||
| + | ===== 2005 ===== | ||
| + | * [[A review and comparison of classification algorithms for medical decision making]] | ||
| + | ===== 2016 ===== | ||
| + | * [[Predicting Breast Cancer Survivability Using Data Mining Techniques]] | ||
| + | |||
| + | |||
| + | |||
| + | === Feature Selection === | ||
| + | ==== Identifying differences ==== | ||
| + | ===== 2017 ===== | ||
| + | * [[Identification of differentially expressed peptides in high-throughput proteomics data]] | ||
| + | * [[In-depth method assessments of differentially expressed protein detection for shotgun proteomics data with missing values]] | ||
| + | ==== Dimension reduction ==== | ||
| + | ===== 2008 ===== | ||
| + | * [[On the Relationship Between Feature Selection and Classification Accuracy]] | ||
| + | ===== 2015 ===== | ||
| + | * [[Comparing feature selection methods for highdimensional imbalanced data: identifying rheumatoid arthritis cohorts from routine data]] | ||
| + | |||
| + | |||
| + | === Imputation methods for missing values === | ||
| + | ===== 2001 ===== | ||
| + | * [[Missing value estimation methods for DNA microarrays]] | ||
| + | ===== 2015 ===== | ||
| + | * [[Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies]] | ||
| + | * [[Multiple imputation and analysis for high-dimensional incomplete proteomics data]] | ||
| + | ===== 2018 ===== | ||
| + | * [[Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data]] | ||
| + | |||
| + | |||
=== ODE-based Modelling === | === ODE-based Modelling === | ||
| + | ===== 2001 ===== | ||
| + | * [[Ways to Fit a PK Model with Some Data Below the Quantification Limit]] | ||
| + | ===== 2008 ===== | ||
* [[Hybrid optimization method with general switching strategy for parameter estimation]] | * [[Hybrid optimization method with general switching strategy for parameter estimation]] | ||
| + | ===== 2013 ===== | ||
* [[Lessons Learned from Quantitative Dynamical Modeling in Systems Biology]] | * [[Lessons Learned from Quantitative Dynamical Modeling in Systems Biology]] | ||
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* [[ODE parameter inference using adaptive gradient matching with Gaussian processes]] | * [[ODE parameter inference using adaptive gradient matching with Gaussian processes]] | ||
| + | ===== 2018 ===== | ||
| + | * [[Benchmarking optimization methods for parameter estimation in large kinetic models]] | ||
| + | |||
| − | === | + | |
| + | === Omics Workflows === | ||
| + | ===== 2017 ===== | ||
| + | * [[A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation]] | ||
| + | |||
| + | |||
| + | |||
| + | === Preprocessing high-throughput data=== | ||
===== 2009 ===== | ===== 2009 ===== | ||
* [[Comparison of Affymetrix data normalization methods using 6,926 experiments across five array generations]] | * [[Comparison of Affymetrix data normalization methods using 6,926 experiments across five array generations]] | ||
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* [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods | * [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods | ||
for Omics Data Sets]] | for Omics Data Sets]] | ||
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Revision as of 12:05, 9 August 2018
Here outcomes of benchmarking studies from the literature are collected. Please extend this list by creating a new page and adding a link below. Use the guidelines described here. The goal is achieving a consensus within the scientific community.
Contents
Results from Literature
Classification
2003
Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
2005
2016
Feature Selection
Identifying differences
2017
- Identification of differentially expressed peptides in high-throughput proteomics data
- In-depth method assessments of differentially expressed protein detection for shotgun proteomics data with missing values
Dimension reduction
2008
2015
Imputation methods for missing values
2001
2015
- Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies
- Multiple imputation and analysis for high-dimensional incomplete proteomics data
2018
ODE-based Modelling
2001
2008
2013
- Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
- ODE parameter inference using adaptive gradient matching with Gaussian processes
2018
Omics Workflows
2017
Preprocessing high-throughput data
2009
2010
2012
2014
- [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods
for Omics Data Sets]]
