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Motivation: Mass spectrometry-based proteomics is among the most commonly used methods for scrutinizing proteomic profiles in different organs for biological or medical researches. All the proteomic analyses including peptide/protein…

Quantitative Methods · Quantitative Biology 2017-11-01 Chunwei Ma

Motivation: Assigning statistical significance accurately has become increasingly important as meta data of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of…

Quantitative Methods · Quantitative Biology 2014-07-25 Gelio Alves , Yi-Kuo Yu

In comparative proteomics studies, LC-MS/MS data is generally quantified using one or both of two measures: the spectral count, derived from the identification of MS/MS spectra, or some measure of ion abundance derived from the LC-MS data.…

Applications · Statistics 2015-03-19 Thomas I. Milac , Timothy W. Randolph , Pei Wang

Product quantization (PQ) is a widely used technique for ad-hoc retrieval. Recent studies propose supervised PQ, where the embedding and quantization models can be jointly trained with supervised learning. However, there is a lack of…

Computation and Language · Computer Science 2021-09-14 Shitao Xiao , Zheng Liu , Yingxia Shao , Defu Lian , Xing Xie

Summary: MALDIquant is an R package providing a complete and modular analysis pipeline for quantitative analysis of mass spectrometry data. MALDIquant is specifically designed with application in clinical diagnostics in mind and implements…

Genomics · Quantitative Biology 2012-08-30 Sebastian Gibb , Korbinian Strimmer

The computational analysis of Mass Spectrometry Imaging (MSI) data aims at the identification of interesting mass co-localizations and the visualization of their lateral distribution in the sample, usually a tissue cross section. But as the…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Karsten Wüllems , Tim W. Nattkemper

Liquid chromatography with tandem mass spectrometry (LC-MS/MS) based proteomics is a well-established research field with major applications such as identification of disease biomarkers, drug discovery, drug design and development. In…

Quantitative Methods · Quantitative Biology 2018-01-08 Fatema Tuz Zohora , Ngoc Hieu Tran , Xianglilan Zhang , Lei Xin , Baozhen Shan , Ming Li

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of…

Liquid Chromatography Mass Spectrometry (LC-MS) is an indispensable analytical technique in proteomics, metabolomics, and other life sciences. While OpenMS provides advanced open-source software for MS data analysis, its complexity can be…

MSstatsQC [3] is an open-source software that provides longitudinal system suitability monitoring tools in the form of control charts for proteomic experiments. It includes simultaneous tools for the mean and dispersion of suitability…

Human-Computer Interaction · Computer Science 2020-03-27 Sara Mohammad Taheri , Omkar Terse , Eralp Dogu , Magy Seif El-Nasr , Olga Vitek

By coupling peptides with DNA tags (i.e., 'barcodes'), it is now possible to harness high-throughput sequencing (HTS) technologies to enable highly multiplexed peptide-based assays, which have a variety of potential applications including…

Quantitative Methods · Quantitative Biology 2020-07-13 Zane W. Fink , Vidal Martinez , John Altin , Jason T. Ladner

Mass spectrometry is a widely used method to study molecules and processes in medicine, life sciences, chemistry, catalysis, and industrial product quality control, among many other applications. One of the main features of some mass…

Chemical Physics · Physics 2024-07-02 Daniil A. Boiko , Valentine P. Ananikov

Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not…

Computation · Statistics 2015-08-04 Andrzej Polanski , Michal Marczyk , Monika Pietrowska , Piotr Widlak , Joanna Polanska

Mass spectrometry-based proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. Though recent years have seen a tremendous improvement in instrument performance and the computational tools used,…

Mass spectrometry (MS) is an important technique for chemical profiling which calculates for a sample a high dimensional histogram-like spectrum. A crucial step of MS data processing is the peak picking which selects peaks containing…

Machine Learning · Statistics 2009-10-05 Theodore Alexandrov , Klaus Steinhorst , Oliver Keszoecze , Stefan Schiffler

Orchestrating parametric fitting of multicomponent spectra at scale is an essential yet underappreciated task in high-throughput quantification of materials and chemical composition. To automate the annotation process for spectroscopic and…

Materials Science · Physics 2021-03-30 Rui Patrick Xian , Ralph Ernstorfer , Philipp Michael Pelz

Methods to visualize the two-dimensional distribution of molecules by mass spectrometric imaging evolve rapidly and yield novel applications in biology, medicine, and material surface sciences. Most mass spectrometric imagers acquire high…

Instrumentation and Detectors · Physics 2011-03-11 Casimir Bamberger , Uwe Renz , Andreas Bamberger

Quantum devices require precisely calibrated analog signals, a process that is complex and time-consuming. Many calibration strategies exist, and all require careful analysis and tuning to optimize system availability. To enable rigorous…

Summary: Mass spectrometry coupled to liquid chromatography (LC-MS/MS) is a powerful technique for the charac-terisation of proteomes. However, the diverse software platforms available for processing the raw proteomics data, each produce…

Fine-tuning large language models (LLMs) using low-rank adaptation (LoRA) has become a highly efficient approach for downstream tasks, particularly in scenarios with limited computational resources. However, applying LoRA techniques to…

Machine Learning · Computer Science 2025-08-15 Yanxia Deng , Aozhong Zhang , Selcuk Gurses , Naigang Wang , Zi Yang , Penghang Yin
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