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1. A comparison of methods for quantifying prediction uncertainty in systems biology
2. A general modular framework for gene set enrichment analysis
3. A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data
4. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies
5. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ
6. An Automated Pipeline for High-Throughput Label-Free Quantitative Proteomics
7. An improved algorithm for peak detection in mass spectra based on continuous wavelet transform
8. Benchmark problems for dynamic modeling of intracellular processes
9. Benchmarking Projects
10. Benchmarking Studies in Computational Biology
11. Benchmarking optimization methods for parameter estimation in large kinetic models
12. Bioinformatics and Statistics: LC‐MS (/MS) Data Preprocessing for Biomarker Discovery
13. Chemometric methods in data processing of mass spectrometry-based metabolomics: A review
14. Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery
15. Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16
16. Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data
17. Comparison of peak‐picking workflows for untargeted liquid chromatography/high‐resolution mass spectrometry metabolomics data analysis
18. Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
19. Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems
20. Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection
21. Concepts for Bechmarking Studies:
22. DMR Calling from BSSEQ:
23. DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts
24. DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data
25. Data-driven normalization strategies for high-throughput quantitative RT-PCR
26. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
27. Data processing has major impact on the outcome of quantitative label-free LC-MS analysis
28. Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus
29. Detecting and overcoming systematic bias in high-throughput screening technologies: a comprehensive review of practical issues and methodological solutions
30. Efficient computation of steady states in large-scale ODE models of biochemical reaction networks
31. Efficient parameterization of large-scale dynamic models based on relative measurements
32. Evaluation of Derivative-Free Optimizers for Parameter Estimation in Systems Biology
33. Evaluation of preprocessing, mapping and postprocessing algorithms for analyzing whole genome bisulfite sequencing data
34. Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data
35. Fast derivatives of likelihood functionals for ODE based models using adjoint-state method
36. Funding
37. Gene set analysis methods: a systematic comparison
38. Getting started with MediaWiki
39. Guidelines for Summarizing a Literature Study
40. Help
41. Hierarchical optimization for the efficient parametrization of ODE models
42. Hybrid optimization method with general switching strategy for parameter estimation
43. Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening
44. Identifying and quantifying metabolites by scoring peaks of GC-MS data
45. Improved Peak Detection and Deconvolution of Native Electrospray Mass Spectra from Large Protein Complexes
46. Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching
47. Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
48. Literature Studies
49. MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid
50. Machine learning methods for predictive proteomics

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