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Showing below up to 50 results in range #51 to #100.

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51. Evaluation of the microba community profiler for taxonomic profiling of metagenomic datasets from the human gut microbiome
52. Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data
53. Fast derivatives of likelihood functionals for ODE based models using adjoint-state method
54. Funding
55. Gene set analysis methods: a systematic comparison
56. Guidelines for Summarizing a Literature Study
57. Help
58. Hierarchical optimization for the efficient parametrization of ODE models
59. Hybrid optimization method with general switching strategy for parameter estimation
60. Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening
61. Identifying and quantifying metabolites by scoring peaks of GC-MS data
62. Improved Peak Detection and Deconvolution of Native Electrospray Mass Spectra from Large Protein Complexes
63. Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching
64. LEMMI: a continuous benchmarking platform for metagenomics classifiers
65. Lessons Learned from Quantitative Dynamical Modeling in Systems Biology
66. Literature Studies
67. MS‐Analyzer: preprocessing and data mining services for proteomics applications on the Grid
68. Machine learning methods for predictive proteomics
69. MeltDB: a software platform for the analysis and integration of metabolomics experiment data
70. MetaboAnalyst: a web server for metabolomic data analysis and interpretation
71. MethCP: Differentially Methylated Region Detection with Change Point Models (bioRxiv)
72. Microbiome differential abundance methods produce different results across 38 datasets
73. Mini-batch optimization enables training of ODE models on large-scale datasets
74. Missing value estimation methods for DNA microarrays
75. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline
76. Mockrobiota: a public resource for microbiome bioinformatics benchmarking
77. NOREVA: normalization and evaluation of MS-based metabolomics data
78. Normalization regarding non-random missing values in high-throughput mass spectrometry data
79. NormalyzerDE: Online Tool for Improved Normalization of Omics Expression Data and High-Sensitivity Differential Expression Analysis
80. OpenMS: a flexible open-source software platform for mass spectrometry data analysis
81. Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis
82. Optimization and uncertainty analysis of ODE models using second order adjoint sensitivity analysis
83. Optimization of miRNA-seq data preprocessing
84. Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach
85. Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy
86. Parameter estimation in models of biological oscillators: an automated regularised estimation approach
87. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis
88. Peak alignment using wavelet pattern matching and differential evolution
89. Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms
90. Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis
91. Performance of objective functions and optimization procedures for parameter estimation in system biology models
92. Predicting Breast Cancer Survivability Using Data Mining Techniques
93. Preprocessing of tandem mass spectrometric data to support automatic protein identification
94. Prevention, diagnosis and treatment of high-throughput sequencing data pathologies
95. Project 20 Benchmark Problems for Modelling Intracellular Processes
96. Project Imputation in Proteomics
97. Recursive partitioning for missing data imputation in the presence of interaction effects
98. Recursive partitioning for missing data imputation in the presence of interaction effects.
99. Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics
100. Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics.

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