Difference between revisions of "Literature Studies"

(Preprocessing high-throughput data)
(Hossein)
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==== Hossein ====
 
==== Hossein ====
  
''' 2020 '''</br>
+
 
*[[Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice]]
 
 
''' 2019 '''</br>
 
''' 2019 '''</br>
 
*[[Benchmark problems for dynamic modeling of intracellular processes]]
 
*[[Benchmark problems for dynamic modeling of intracellular processes]]
 
*[[Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach]]
 
*[[Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach]]
*[[Benchmark problems for dynamic modeling of intracellular processes]]
 
*[[Continuous analogue to iterative optimization for PDE-constrained inverse problems]]
 
*[[Model validation in dynamic systems for time-course data with complex error structures]]
 
 
*[[Tracking for parameter and state estimation in possibly misspecified partially observed linear Ordinary Differential Equations]]
 
*[[Tracking for parameter and state estimation in possibly misspecified partially observed linear Ordinary Differential Equations]]
 
*[[Efficient computation of steady states in large-scale ODE models of biochemical reaction networks]]
 
*[[Efficient computation of steady states in large-scale ODE models of biochemical reaction networks]]
 
*[[Statistical Model Checking-Based Analysis of Biological Networks]]
 
*[[Statistical Model Checking-Based Analysis of Biological Networks]]
 +
<a href="http://www.w3.org">W3C organization website</a>
 
''' 2018 '''</br>
 
''' 2018 '''</br>
 
*[[Hierarchical optimization for the efficient parametrization of ODE models]]
 
*[[Hierarchical optimization for the efficient parametrization of ODE models]]

Revision as of 09:42, 25 February 2020

Page summary
Here outcomes of benchmarking studies from the literature are collected. The primary aim is a comprehensive overview about neutral benchmark studies, i.e. assessments which were performed independenty on publication of a new approach. Studies which are not neutral are put in brackets.

The focus is on computational methods for analyzing experimental data (instead of comparing experimental techniques or platforms).

Please extend this list by creating a new page and adding a link below.
Use the guidelines described here.

1 Results from Literature

1.1 Classification

2003

2005

2016

1.2 Selection of Differential Features and Regions

1.2.1 Identifying differential features

2006

2010

2017

2018

1.2.2 Identifying differential regions (e.g. DMRs)

2015

2016

2017

2018

1.2.3 Identifying sets of features (e.g. gene set analyses)

2009

A general modular framework for gene set enrichment analysis

2018

Gene set analysis methods: a systematic comparison

1.2.4 Dimension reduction

2008

2015

1.3 Imputation methods for missing values

2001

2016

2018

1.4 ODE-based Modelling

2001

2008

2011

2013

2018

2020

1.4.1 Hossein

2019

<a href="http://www.w3.org">W3C organization website</a> 2018

2017

1.4.2 Tim

2017


2018

1.4.3 Fabian

2019

1.4.4 Lukas

2017

2018

2019

2020

1.5 Omics Workflows

2015

2017

2019


1.6 Preprocessing high-throughput data

2003

2005

2006

2007

2008

2009

2010

2011

2012

2014