Difference between revisions of "Literature Studies"
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*[[Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice]] | *[[Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice]] | ||
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*[[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]] | ||
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*[[An easy and efficient approach for testing identifiability]] | *[[An easy and efficient approach for testing identifiability]] | ||
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| + | *[[Local Identifiability Analysis of NonLinear ODE Models: How to Determine All Candidate Solutions]] | ||
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| + | *[[Fast derivatives of likelihood functionals for ODE based models using adjoint-state method]] | ||
==== Tim ==== | ==== Tim ==== | ||
Revision as of 09:23, 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. |
Contents
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
- 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
- Strategies for analyzing bisulfite sequencing data
2018
1.2.2 Identifying differential regions (e.g. DMRs)
2015
- De novo identification of differentially methylated regions in the human genome
- MethylAction: detecting differentially methylated regions that distinguish biological subtypes
- metilene: Fast and sensitive calling of differentially methylated regions from bisulfite sequencing data
2016
- seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data
- Statistical methods for detecting differentially methylated regions based on MethylCap-seq data
2017
2018
- Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus
- DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts
- MethCP: Differentially Methylated Region Detection with Change Point Models (bioRxiv)
1.2.3 Identifying sets of features (e.g. gene set analyses)
2018
Gene set analysis methods: a systematic comparison
1.2.4 Dimension reduction
2008
2015
1.3 Imputation methods for missing values
2001
2016
- 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
2011
2013
- Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
- ODE parameter inference using adaptive gradient matching with Gaussian processes
2018
2020
1.4.1 Hossein
2020
2019
- 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
- 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
- Efficient computation of steady states in large-scale ODE models of biochemical reaction networks
- Statistical Model Checking-Based Analysis of Biological Networks
2018
- Hierarchical optimization for the efficient parametrization of ODE models
- Inference for differential equation models using relaxation via dynamical systems
- Identification of parameters in systems biology
- Continuous analogue to iterative optimization for PDE-constrained inverse problems
- An easy and efficient approach for testing identifiability
- Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis
- Local Identifiability Analysis of NonLinear ODE Models: How to Determine All Candidate Solutions
2017
1.4.2 Tim
2017
2018
1.4.3 Fabian
2019
- Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models
- A comparison of methods for quantifying prediction uncertainty in systems biology
- Parameter estimation in models of biological oscillators: an automated regularised estimation approach
1.4.4 Lukas
2017
2018
- Optimization and uncertainty analysis of ODE models using second order adjoint sensitivity analysis
- Evaluation of Derivative-Free Optimizers for Parameter Estimation in Systems Biology
1.5 Omics Workflows
2015
2017
- A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation
- A benchmarking of workflows for detecting differential splicing and differential expression at isoform level in human RNA-seq studies
2019
- A Systematic Evaluation of Single CellRNA-Seq Analysis Pipelines
- Benchmarking workflows to assess performance and suitability of germline variant calling pipelines in clinical diagnostic assays
1.6 Preprocessing high-throughput data
2003
2005
- Comparison of Affymetrix GeneChip Expression Measures
- Comparison of background correction and normalization procedures for high-density oligonucleotide microarrays
2006
2008
2009
2010
- Consistency of predictive signature genes and classifiers generated using different microarray platforms
- Detecting and correcting systematic variation in large-scale RNA sequencing data
- Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
- Normalization of RNA-seq data using factor analysis of control genes or samples
2011
2012
2014
