Statistical and Computational Methods for Comparing High ...

Author(s): Ge, Xinzhou | Advisor(s): Li, Jingyi J | Abstract: The development of high-throughput biological technologies have enabled researchers to ...

We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify ...

Computational and Statistical Methods for High-Throughput Mass ...

Computational and Statistical Methods for High-Throughput Mass Spectrometry-Based PTM Analysis ... Methods Mol Biol. 2017:1558:437-458. doi: 10.1007/978-1-4939- ...

Statistical and Computational Methods for Differential Expression ...

Statistical and Computational Methods for Differential Expression Analysis in High-throughput Gene Expression Data ... comparing with existing methods ...

Statistical and computational methods for comparative proteomic ...

Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry ... high-level processing steps ...

Statistical and Computational Methods for Comparative Proteomic ...

High-throughput MS/MS offers a powerful means of analyzing biological samples. However, MS/MS is time consuming, adding an order of magnitude in time to a ...

Statistical and computational methods for integrating microbiome ...

A major disadvantage in applying CCA to omics data is that such data is typically high dimensional. This is a limitation as CCA typically ...

Comparison of computational methods for Hi-C data analysis - Nature

We quantitatively compared the performance of 13 algorithms in their analyses of Hi-C data from six landmark studies and simulations.

Statistical and Computational Methods for Microbiome Multi-Omics ...

To this end, many of the articles in this Research Topic focus on new ways to analyze and integrate multi-table data using cutting-edge statistical and ...

Statistical analysis of high-dimensional biomedical data: a gentle ...

Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time ...

Statistical and Computational Methods for Genetic Diseases: An ...

The aim of the paper is to provide an overview of statistical and computational methods paying attention to methods for the sequence analysis and complex ...

Comparison of computational methods for high dimensional item ...

Metropolis-Hastings Robbins-Monro algorithm for con- firmatory item factor analysis. Journal of Educational and Behavioral. Statistics, 35, ...

Comparison of computational methods for Hi-C data analysis

We quantitatively compared the performance of 13 algorithms in their analyses of Hi-C data from six landmark studies and simulations.

Comparison of computational methods for 3D genome analysis at ...

Highlights · Overall, proper analysis methods for single-cell Hi-C remain elusive. · Compartments may be a statistical feature emerging from the ...

COMPUTATIONAL METHODS IN STATISTICS

high. Some functions will have the first term much larger than ... Comparing this relation with the singular value decomposition of the ...

Computational methods - (Theoretical Statistics) - Fiveable

Compare and contrast different computational methods used in statistical analysis, specifically in the context of random vector transformations. Different ...

Comparison of computational methods for high dimensional item ...

A simulation study is conducted to compare maximum likelihood estimation based on Montecarlo integration, maximum likelihood estimations based on ...

What is the difference between computational statistics and machine ...

Computational statistics, machine learning, and statistical analysis of big data are distinct but interconnected fields.

Computational and Statistical Models: A Comparison for Policy ...

Statistical models are reductionist approaches geared towards proving the null hypothesis. While these two approaches may seem contrary to each other, we ...

An evaluation of computational methods for aggregate data meta ...

Accordingly, on average, the AGHQ had the highest convergence rate but the longest computing time compared to the two methods. We also observed ...