A review on quantitative multiplexed proteomics

N Pappireddi, L Martin, M Wühr - Chembiochem, 2019‏ - Wiley Online Library
Over the last few decades, mass spectrometry‐based proteomics has become an
increasingly powerful tool that is now able to routinely detect and quantify thousands of …

Machine learning applications for mass spectrometry-based metabolomics

UW Liebal, ANT Phan, M Sudhakar, K Raman… - Metabolites, 2020‏ - mdpi.com
The metabolome of an organism depends on environmental factors and intracellular
regulation and provides information about the physiological conditions. Metabolomics helps …

[HTML][HTML] Pan-cancer proteomic map of 949 human cell lines

E Gonçalves, RC Poulos, Z Cai, S Barthorpe… - Cancer Cell, 2022‏ - cell.com
The proteome provides unique insights into disease biology beyond the genome and
transcriptome. A lack of large proteomic datasets has restricted the identification of new …

Bioinformatics methods for mass spectrometry-based proteomics data analysis

C Chen, J Hou, JJ Tanner, J Cheng - International journal of molecular …, 2020‏ - mdpi.com
Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous
progress in the understanding of cellular mechanisms, disease progression, and the …

The impact of nanoparticle protein corona on cytotoxicity, immunotoxicity and target drug delivery

C Corbo, R Molinaro, A Parodi… - …, 2016‏ - Taylor & Francis
In a perfect sequence of events, nanoparticles (NPs) are injected into the bloodstream
where they circulate until they reach the target tissue. The ligand on the NP surface …

Accounting for the multiple natures of missing values in label-free quantitative proteomics data sets to compare imputation strategies

C Lazar, L Gatto, M Ferro, C Bruley… - Journal of proteome …, 2016‏ - ACS Publications
Missing values are a genuine issue in label-free quantitative proteomics. Recent works have
surveyed the different statistical methods to conduct imputation and have compared them on …

WGCNA application to proteomic and metabolomic data analysis

G Pei, L Chen, W Zhang - Methods in enzymology, 2017‏ - Elsevier
Progresses in mass spectrometric instrumentation and bioinformatics identification
algorithms made over the past decades allow quantitative measurements of relative or …

Machine learning and feature selection for drug response prediction in precision oncology applications

M Ali, T Aittokallio - Biophysical reviews, 2019‏ - Springer
In-depth modeling of the complex interplay among multiple omics data measured from
cancer cell lines or patient tumors is providing new opportunities toward identification of …

Phosphoproteomics in the age of rapid and deep proteome profiling

NM Riley, JJ Coon - Analytical chemistry, 2016‏ - ACS Publications
Protein phosphorylation is a post-translational modification (PTM) that orchestrates a diverse
array of cellular processes. Because this modification serves as a rapid and reversible …

Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: a comparative study

M Kokla, J Virtanen, M Kolehmainen, J Paananen… - BMC …, 2019‏ - Springer
Background LC-MS technology makes it possible to measure the relative abundance of
numerous molecular features of a sample in single analysis. However, especially non …