Pages without language links

The following pages do not link to other language versions.

Showing below up to 20 results in range #21 to #40.

View (previous 20 | next 20) (20 | 50 | 100 | 250 | 500)

  1. Benchmarking of 16S rRNA gene databases using known strain sequences
  2. Benchmarking optimization methods for parameter estimation in large kinetic models
  3. Bioinformatics and Statistics: LC‐MS (/MS) Data Preprocessing for Biomarker Discovery
  4. Catalyst: Fast and flexible modeling of reaction networks
  5. Chemometric methods in data processing of mass spectrometry-based metabolomics: A review
  6. Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery
  7. Comparative study of classifiers for human microbiome data
  8. Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16
  9. Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data
  10. Comparison of peak‐picking workflows for untargeted liquid chromatography/high‐resolution mass spectrometry metabolomics data analysis
  11. Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data
  12. Comprehensive benchmarking and ensemble approaches for metagenomic classifiers
  13. Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems
  14. Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection
  15. Concepts for Bechmarking Studies:
  16. DMR Calling from BSSEQ:
  17. DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts
  18. DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data
  19. Data-driven normalization strategies for high-throughput quantitative RT-PCR
  20. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

View (previous 20 | next 20) (20 | 50 | 100 | 250 | 500)