AIMC Topic: Mass Spectrometry
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Characterization of phenolic compounds and aroma active compounds in feijoa juice from four New Zealand grown cultivars by LC-MS and HS-SPME-GC-O-MS.
Food research international (Ottawa, Ont.)
Dec 5, 2019
The phenolic compounds and aroma active compounds in feijoa (Acca sellowiana (O.Berg) Burret) juice from four New Zealand grown cultivars (Apollo, Unique, Opal Star, and Wiki Tu) were investigated. A high total phenolic content (maximum 1.89 mg GAE/m...
Machine learning distilled metabolite biomarkers for early stage renal injury.
Metabolomics : Official journal of the Metabolomic Society
Dec 5, 2019
INTRODUCTION: With chronic kidney disease (CKD), kidney becomes damaged overtime and fails to clean blood. Around 15% of US adults have CKD and nine in ten adults with CKD do not know they have it.
Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.
Journal of cutaneous pathology
Nov 27, 2019
PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which ...
DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.
Nature methods
Nov 25, 2019
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves t...
Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.
Mass spectrometry reviews
Oct 11, 2019
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a larg...
Automating Complex, Multistep Processes on a Single Robotic Platform to Generate Reproducible Phosphoproteomic Data.
SLAS discovery : advancing life sciences R & D
Sep 26, 2019
Mass spectrometry-based phosphoproteomics holds promise for advancing drug treatment and disease diagnosis; however, its clinical translation has thus far been limited. This is in part due to an unstandardized and segmented sample preparation process...
Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.
Analytica chimica acta
Sep 25, 2019
Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absen...
Deep Neural Networks for Classification of LC-MS Spectral Peaks.
Analytical chemistry
Sep 19, 2019
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
Aug 28, 2019
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
Jul 17, 2019
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...
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