Machine learning meets omics: applications and perspectives

R Li, L Li, Y Xu, J Yang - Briefings in Bioinformatics, 2022 - academic.oup.com
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 …

[HTML][HTML] Single-cell metabolomics: where are we and where are we going?

I Lanekoff, VV Sharma, C Marques - Current opinion in biotechnology, 2022 - Elsevier
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 …

Fully automated unconstrained analysis of high-resolution mass spectrometry data with machine learning

DA Boiko, KS Kozlov, JV Burykina… - Journal of the …, 2022 - ACS Publications
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 …

An ensemble method of the machine learning to prognosticate the gastric cancer

H Baradaran Rezaei, A Amjadian, MV Sebt… - Annals of Operations …, 2023 - Springer
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 …

Recent developments in machine learning for mass spectrometry

AG Beck, M Muhoberac, CE Randolph… - ACS Measurement …, 2024 - ACS Publications
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 …

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 …

Lipid heterogeneity between astrocytes and neurons revealed by single‐cell MALDI‐MS combined with immunocytochemical classification

EK Neumann, TJ Comi, SS Rubakhin… - Angewandte …, 2019 - Wiley Online Library
Transcriptomics characterizes cells based on their potential molecular repertoire whereas
direct mass spectrometry (MS) provides information on the actual compounds present within …

[HTML][HTML] Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer

B Bueschbell, AB Caniceiro, PMS Suzano… - Drug Resistance …, 2022 - Elsevier
Globally with over 10 million deaths per year, cancer is the most transversal disease across
countries, cultures, and ethnicities, affecting both developed and develo** regions …

Chemical strategies to overcome resistance against targeted anticancer therapeutics

R Pisa, TM Kapoor - Nature chemical biology, 2020 - nature.com
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 …

Artificial Intelligence-based management of adult chronic myeloid leukemia: where are we and where are we going?

S Bernardi, M Vallati, R Gatta - Cancers, 2024 - mdpi.com
Simple Summary The field of artificial intelligence (AI) is quickly becoming recognized for its
potential to significantly improve medicine. AI is still in its infancy when it comes to treating …