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Showing below up to 50 results in range #1 to #50.

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  1. DMR Calling from BSSEQ:‏‎ (13:53, 7 August 2018)
  2. Concepts for Bechmarking Studies:‏‎ (15:06, 7 August 2018)
  3. Funding‏‎ (11:32, 9 August 2018)
  4. Project Imputation in Proteomics‏‎ (14:30, 9 August 2018)
  5. Benchmarking Studies in Computational Biology‏‎ (05:40, 10 August 2018)
  6. Getting started with MediaWiki‏‎ (05:41, 10 August 2018)
  7. Benchmarking Projects‏‎ (05:46, 10 August 2018)
  8. Project 20 Benchmark Problems for Modelling Intracellular Processes‏‎ (08:52, 10 August 2018)
  9. Benchmarking optimization methods for parameter estimation in large kinetic models‏‎ (08:20, 18 June 2019)
  10. Optimization and uncertainty analysis of ODE models using second order adjoint sensitivity analysis‏‎ (08:47, 25 February 2020)
  11. Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data‏‎ (09:42, 25 February 2020)
  12. Chemometric methods in data processing of mass spectrometry-based metabolomics: A review‏‎ (10:00, 25 February 2020)
  13. Optimization of miRNA-seq data preprocessing‏‎ (10:05, 25 February 2020)
  14. TEMPLATE‏‎ (10:18, 25 February 2020)
  15. Detecting and overcoming systematic bias in high-throughput screening technologies: a comprehensive review of practical issues and methodological solutions‏‎ (10:22, 25 February 2020)
  16. Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening‏‎ (10:29, 25 February 2020)
  17. Prevention, diagnosis and treatment of high-throughput sequencing data pathologies‏‎ (10:39, 25 February 2020)
  18. Help‏‎ (10:42, 25 February 2020)
  19. Normalization regarding non-random missing values in high-throughput mass spectrometry data‏‎ (10:52, 25 February 2020)
  20. Guidelines for Summarizing a Literature Study‏‎ (11:37, 25 February 2020)
  21. DMRfinder: efficiently identifying differentially methylated regions from MethylC-seq data‏‎ (11:37, 25 February 2020)
  22. Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus‏‎ (11:38, 25 February 2020)
  23. DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts‏‎ (11:38, 25 February 2020)
  24. MethCP: Differentially Methylated Region Detection with Change Point Models (bioRxiv)‏‎ (11:38, 25 February 2020)
  25. Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes‏‎ (11:41, 25 February 2020)
  26. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline‏‎ (11:45, 25 February 2020)
  27. Recursive partitioning for missing data imputation in the presence of interaction effects.‏‎ (11:48, 25 February 2020)
  28. Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics.‏‎ (11:49, 25 February 2020)
  29. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies‏‎ (11:50, 25 February 2020)
  30. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis‏‎ (11:51, 25 February 2020)
  31. Lessons Learned from Quantitative Dynamical Modeling in Systems Biology‏‎ (11:52, 25 February 2020)
  32. Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems‏‎ (11:53, 25 February 2020)
  33. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models‏‎ (11:53, 25 February 2020)
  34. Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy‏‎ (11:54, 25 February 2020)
  35. Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks‏‎ (11:57, 25 February 2020)
  36. MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid‏‎ (12:07, 25 February 2020)
  37. Efficient computation of steady states in large-scale ODE models of biochemical reaction networks‏‎ (12:12, 25 February 2020)
  38. Parameter estimation in models of biological oscillators: an automated regularised estimation approach‏‎ (12:13, 25 February 2020)
  39. An Automated Pipeline for High-Throughput Label-Free Quantitative Proteomics‏‎ (12:25, 25 February 2020)
  40. Comparative evaluation of preprocessing freeware on chromatography/mass spectrometry data for signature discovery‏‎ (12:56, 25 February 2020)
  41. Comparison of peak‐picking workflows for untargeted liquid chromatography/high‐resolution mass spectrometry metabolomics data analysis‏‎ (13:02, 25 February 2020)
  42. Comparing gene set analysis methods on single-nucleotide polymorphism data from Genetic Analysis Workshop 16‏‎ (13:03, 25 February 2020)
  43. Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection‏‎ (13:06, 25 February 2020)
  44. Data-driven normalization strategies for high-throughput quantitative RT-PCR‏‎ (13:29, 25 February 2020)
  45. Performance of objective functions and optimization procedures for parameter estimation in system biology models‏‎ (13:38, 25 February 2020)
  46. Machine learning methods for predictive proteomics‏‎ (13:46, 25 February 2020)
  47. Gene set analysis methods: a systematic comparison‏‎ (13:54, 25 February 2020)
  48. The effects of nonignorable missing data on label-free mass spectrometry proteomics experiments‏‎ (13:56, 25 February 2020)
  49. Software platform for high-throughput glycomics‏‎ (13:58, 25 February 2020)
  50. MeltDB: a software platform for the analysis and integration of metabolomics experiment data‏‎ (14:04, 25 February 2020)

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