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- Benchmarking of 16S rRNA gene databases using known strain sequences
- Benchmarking optimization methods for parameter estimation in large kinetic models
- Bioinformatics and Statistics: LC‐MS (/MS) Data Preprocessing for Biomarker Discovery
- Catalyst: Fast and flexible modeling of reaction networks
- Chemometric methods in data processing of mass spectrometry-based metabolomics: A review
- Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery
- Comparative study of classifiers for human microbiome data
- Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16
- Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data
- Comparison of peak‐picking workflows for untargeted liquid chromatography/high‐resolution mass spectrometry metabolomics data analysis
- Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
- Comprehensive benchmarking and ensemble approaches for metagenomic classifiers
- Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems
- Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection
- Concepts for Bechmarking Studies:
- DMR Calling from BSSEQ:
- DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts
- DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data
- Data-driven normalization strategies for high-throughput quantitative RT-PCR
- Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
- Data processing has major impact on the outcome of quantitative label-free LC-MS analysis
- Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus
- Denoising the Denoisers: an independent evaluation of microbiome sequence error-correction approaches
- Detecting and overcoming systematic bias in high-throughput screening technologies: a comprehensive review of practical issues and methodological solutions
- Distribution-based comprehensive evaluation of methods for differential expression analysis in metatranscriptomics
- Efficient computation of steady states in large-scale ODE models of biochemical reaction networks
- Efficient parameterization of large-scale dynamic models based on relative measurements
- Evaluating supervised and unsupervised background noise correction in human gut microbiome data
- Evaluation of Derivative-Free Optimizers for Parameter Estimation in Systems Biology
- Evaluation of preprocessing, mapping and postprocessing algorithms for analyzing whole genome bisulfite sequencing data
- Evaluation of the microba community profiler for taxonomic profiling of metagenomic datasets from the human gut microbiome
- Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data
- Fast derivatives of likelihood functionals for ODE based models using adjoint-state method
- Funding
- Gene set analysis methods: a systematic comparison
- Guidelines for Summarizing a Literature Study
- Help
- Hierarchical optimization for the efficient parametrization of ODE models
- Hybrid optimization method with general switching strategy for parameter estimation
- Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening
- Identifying and quantifying metabolites by scoring peaks of GC-MS data
- Improved Peak Detection and Deconvolution of Native Electrospray Mass Spectra from Large Protein Complexes
- Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching
- LEMMI: a continuous benchmarking platform for metagenomics classifiers
- Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
- Literature Studies
- MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid
- Machine learning methods for predictive proteomics
- MeltDB: a software platform for the analysis and integration of metabolomics experiment data
- MetaboAnalyst: a web server for metabolomic data analysis and interpretation