# Difference between revisions of "Literature Studies"

(Years in bold face instead of headings) |
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=== Classification === | === Classification === | ||

− | + | ''' 2003 ''' | |

Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data | Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data | ||

− | + | ''' 2005 '''</br> | |

* [[A review and comparison of classification algorithms for medical decision making]] | * [[A review and comparison of classification algorithms for medical decision making]] | ||

− | + | ''' 2016 '''</br> | |

* [[Predicting Breast Cancer Survivability Using Data Mining Techniques]] | * [[Predicting Breast Cancer Survivability Using Data Mining Techniques]] | ||

Line 19: | Line 19: | ||

=== Feature Selection === | === Feature Selection === | ||

==== Identifying differences ==== | ==== Identifying differences ==== | ||

− | + | ''' 2017 '''</br> | |

* [[Identification of differentially expressed peptides in high-throughput proteomics data]] | * [[Identification of differentially expressed peptides in high-throughput proteomics data]] | ||

− | * [[In-depth method assessments of | + | * [[In-depth method assessments of di?erentially expressed protein detection for shotgun proteomics data with missing values]] |

==== Dimension reduction ==== | ==== Dimension reduction ==== | ||

− | + | ''' 2008 '''</br> | |

* [[On the Relationship Between Feature Selection and Classification Accuracy]] | * [[On the Relationship Between Feature Selection and Classification Accuracy]] | ||

− | + | ''' 2015 '''</br> | |

* [[Comparing feature selection methods for highdimensional imbalanced data: identifying rheumatoid arthritis cohorts from routine data]] | * [[Comparing feature selection methods for highdimensional imbalanced data: identifying rheumatoid arthritis cohorts from routine data]] | ||

=== Imputation methods for missing values === | === Imputation methods for missing values === | ||

− | + | ''' 2001 '''</br> | |

* [[Missing value estimation methods for DNA microarrays]] | * [[Missing value estimation methods for DNA microarrays]] | ||

− | + | ''' 2015 '''</br> | |

* [[Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies]] | * [[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]] | * [[Multiple imputation and analysis for high-dimensional incomplete proteomics data]] | ||

− | + | ''' 2018 '''</br> | |

* [[Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data]] | * [[Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data]] | ||

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=== ODE-based Modelling === | === ODE-based Modelling === | ||

− | + | ''' 2001 '''</br> | |

* [[Ways to Fit a PK Model with Some Data Below the Quantification Limit]] | * [[Ways to Fit a PK Model with Some Data Below the Quantification Limit]] | ||

− | + | ''' 2008 '''</br> | |

* [[Hybrid optimization method with general switching strategy for parameter estimation]] | * [[Hybrid optimization method with general switching strategy for parameter estimation]] | ||

− | + | ''' 2013 '''</br> | |

* [[Lessons Learned from Quantitative Dynamical Modeling in Systems Biology]] | * [[Lessons Learned from Quantitative Dynamical Modeling in Systems Biology]] | ||

* [[ODE parameter inference using adaptive gradient matching with Gaussian processes]] | * [[ODE parameter inference using adaptive gradient matching with Gaussian processes]] | ||

− | + | ''' 2018 '''</br> | |

* [[Benchmarking optimization methods for parameter estimation in large kinetic models]] | * [[Benchmarking optimization methods for parameter estimation in large kinetic models]] | ||

Line 54: | Line 54: | ||

=== Omics Workflows === | === Omics Workflows === | ||

− | + | ''' 2017 '''</br> | |

* [[A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation]] | * [[A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation]] | ||

Line 60: | Line 60: | ||

=== Preprocessing high-throughput data=== | === Preprocessing high-throughput data=== | ||

− | + | ''' 2009 '''</br> | |

* [[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]] | ||

− | + | ''' 2010 '''</br> | |

* [[Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments]] | * [[Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments]] | ||

− | + | ''' 2012 '''</br> | |

* [[A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis]] | * [[A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis]] | ||

− | + | ''' 2014 '''</br> | |

* [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]] | * [[Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets]] |

## Revision as of 13:27, 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 theguidelines described here. The goal is achieving a consensus within the scientific community.

## Contents

## 1 Results from Literature

### 1.1 Classification

** 2003 **
Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
** 2005 **

** 2016 **

### 1.2 Feature Selection

#### 1.2.1 Identifying differences

** 2017 **

- Identification of differentially expressed peptides in high-throughput proteomics data
- In-depth method assessments of di?erentially expressed protein detection for shotgun proteomics data with missing values

#### 1.2.2 Dimension reduction

** 2008 **

** 2015 **

### 1.3 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 **

### 1.4 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 **

### 1.5 Omics Workflows

** 2017 **

### 1.6 Preprocessing high-throughput data

** 2009 **

** 2010 **

** 2012 **

** 2014 **