Machine learning meets omics: applications and perspectives
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
[HTML][HTML] Single-cell metabolomics: where are we and where are we going?
Single-cell metabolomics with mass spectrometry enables a large variety of metabolites to
be simultaneously detected from individual cells, without any preselection or labelling, to …
be simultaneously detected from individual cells, without any preselection or labelling, to …
Fully automated unconstrained analysis of high-resolution mass spectrometry data with machine learning
Mass spectrometry (MS) is a convenient, highly sensitive, and reliable method for the
analysis of complex mixtures, which is vital for materials science, life sciences fields such as …
analysis of complex mixtures, which is vital for materials science, life sciences fields such as …
Recent developments in machine learning for mass spectrometry
Statistical analysis and modeling of mass spectrometry (MS) data have a long and rich
history with several modern MS-based applications using statistical and chemometric …
history with several modern MS-based applications using statistical and chemometric …
An ensemble method of the machine learning to prognosticate the gastric cancer
Gastric Cancer is the most common malignancy of the digestive tract, which is the third
leading cause of cancer-related mortality worldwide. The early prognosis methods …
leading cause of cancer-related mortality worldwide. The early prognosis methods …
AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications
LM Petrick, N Shomron - Cell Reports Physical Science, 2022 - cell.com
Metabolomics describes a high-throughput approach for measuring a repertoire of
metabolites and small molecules in biological samples. One utility of untargeted …
metabolites and small molecules in biological samples. One utility of untargeted …
Lipid heterogeneity between astrocytes and neurons revealed by single‐cell MALDI‐MS combined with immunocytochemical classification
Transcriptomics characterizes cells based on their potential molecular repertoire whereas
direct mass spectrometry (MS) provides information on the actual compounds present within …
direct mass spectrometry (MS) provides information on the actual compounds present within …
Engineering in medicine to address the challenge of cancer drug resistance: from micro-and nanotechnologies to computational and mathematical modeling
Drug resistance has profoundly limited the success of cancer treatment, driving relapse,
metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies …
metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies …
Chemical strategies to overcome resistance against targeted anticancer therapeutics
Emergence of resistance is a major factor limiting the efficacy of molecularly targeted
anticancer drugs. Understanding the specific mutations, or other genetic or cellular changes …
anticancer drugs. Understanding the specific mutations, or other genetic or cellular changes …
Single-cell mass spectrometry enables insight into heterogeneity in infectious disease
Cellular heterogeneity is generally overlooked in infectious diseases. In this study, we
investigated host cell heterogeneity during infection with Trypanosoma cruzi (T. cruzi) …
investigated host cell heterogeneity during infection with Trypanosoma cruzi (T. cruzi) …