[analysis] Compressive and reductive analysis of genomic and proteomics data

1. 22nd IEEE International Workshop on High Performance Computational Biology (HiCOMB 2023)

2. Benchmarking mass spectrometry based proteomics algorithms using a simulated database

3. Slm-transform: A method for memory-efficient indexing of spectra for database search in lc-ms/ms proteomics

4. High-Performance Reductive Strategies for Big Data from LC-MS/MS Proteomics

5. MaSS‐Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms

6. GPU-DAEMON: GPU algorithm design, data management & optimization template for array based big omics data

7. GPU-PCC: A GPU Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Big fMRI Data

8. An out-of-core gpu based dimensionality reduction algorithm for big mass spectrometry data and its application in bottom-up proteomics

9. Reductive Analytics on Big MS Data leads to tremendous reduction in time for peptide deduction

10. MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing

11. GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

12. On the sampling of big mass spectrometry data