AIMC Topic: Mass Spectrometry

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Deep Neural Networks for Classification of LC-MS Spectral Peaks.

Analytical chemistry
Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has emerged as a valuable tool for biological discovery, capable of assaying thousands of diverse chemical entities in a single biospecimen. Processing of nontargeted LC-MS spectral d...

Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction.

Trends in biotechnology
Metabolomics is a powerful tool to rationally guide the metabolic engineering of synthetic bioproduction pathways. Current reports indicate great potential to further develop metabolomics-directed synthetic bioproduction. Advanced mass metabolomics m...

Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data.

Journal of proteome research
Deep learning (DL), a type of machine learning approach, is a powerful tool for analyzing large sets of data that are derived from biomedical sciences. However, it remains unknown whether DL is suitable for identifying contributing factors, such as b...

Supervised Learning and Mass Spectrometry Predicts the Fate of Nanomaterials.

ACS nano
The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. He...

Predicting Ion Mobility Collision Cross-Sections Using a Deep Neural Network: DeepCCS.

Analytical chemistry
Untargeted metabolomic measurements using mass spectrometry are a powerful tool for uncovering new small molecules with environmental and biological importance. The small molecule identification step, however, still remains an enormous challenge due ...

Metabolomics Analysis in Acute Paraquat Poisoning Patients Based on UPLC-Q-TOF-MS and Machine Learning Approach.

Chemical research in toxicology
Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a bloo...

Streamlining Quality Review of Mass Spectrometry Data in the Clinical Laboratory by Use of Machine Learning.

Archives of pathology & laboratory medicine
CONTEXT.—: Turnaround time and productivity of clinical mass spectrometric (MS) testing are hampered by time-consuming manual review of the analytical quality of MS data before release of patient results.

Automated online coupling of robot-assisted single drop microextraction and liquid chromatography.

Journal of chromatography. A
A high-throughput and innovative setup has been developed to automate the online integration of single drop microextraction (SDME), liquid chromatography (LC) and high-resolution mass spectrometry (QqToF). SDME and LC were online hyphenated for the f...

Comprehensive and Empirical Evaluation of Machine Learning Algorithms for Small Molecule LC Retention Time Prediction.

Analytical chemistry
Liquid chromatography is a core component of almost all mass spectrometric analyses of (bio)molecules. Because of the high-throughput nature of mass spectrometric analyses, the interpretation of these chromatographic data increasingly relies on infor...