AIMC Topic: Metabolomics
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Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches.
Briefings in bioinformatics
Nov 27, 2019
Metabolomics involves studies of a great number of metabolites, which are small molecules present in biological systems. They play a lot of important functions such as energy transport, signaling, building block of cells and inhibition/catalysis. Und...
Multi-omics integration-a comparison of unsupervised clustering methodologies.
Briefings in bioinformatics
Jul 19, 2019
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...
Artificial intelligence and amniotic fluid multiomics: prediction of perinatal outcome in asymptomatic women with short cervix.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jul 1, 2019
OBJECTIVE: To evaluate the application of artificial intelligence (AI), i.e. deep learning and other machine-learning techniques, to amniotic fluid (AF) metabolomics and proteomics, alone and in combination with sonographic, clinical and demographic ...
Young Adult
Adult
Sensitivity and Specificity
Adolescent
Retrospective Studies
Pregnancy
Female
Cervix Uteri
Metabolomics
Predictive Value of Tests
Pregnancy Trimester, Second
Ultrasonography
Pregnancy Outcome
Proteomics
Humans
Artificial Intelligence
Cervical Length Measurement
Amniotic Fluid
Intensive Care Units, Neonatal
Amniocentesis
Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.
Chemical communications (Cambridge, England)
Jan 10, 2019
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...
Ensemble Based Approach for Time Series Classification in Metabolomics.
Studies in health technology and informatics
Jan 1, 2019
BACKGROUND: Machine learning is one important application in the area of health informatics, however classification methods for longitudinal data are still rare.
Machine Learning in Untargeted Metabolomics Experiments.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Machine learning is a form of artificial intelligence (AI) that provides computers with the ability to learn generally without being explicitly programmed. Machine learning refers to the ability of computer programs to adapt when exposed to new data....
Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana.
Molecular omics
Dec 3, 2018
Abiotic stress exposure of plants induces metabolic reprogramming which is tightly regulated by signalling cascades connecting transcriptional with translational and metabolic regulation. Complexity of such interconnected metabolic networks impedes t...
Metabonomics of d-glucaro-1,4-lactone in preventing diethylnitrosamine-induced liver cancer in rats.
Pharmaceutical biology
Dec 1, 2018
CONTEXT: d-Glucaro-1,4-lactone (1,4-GL) exists in many vegetables and fruits. Metabonomics has not been used to investigate the role of 1,4-GL in preventing liver cancer.
IMass Time: The Future, in Future!
Omics : a journal of integrative biology
Nov 1, 2018
Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been...
Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Osteosarcoma is the most common type of bone cancer. The primary means of osteosarcoma diagnosis is through evaluating plain x-rays. Using image analysis techniques, features that clinicians use to diagnose osteosarcoma can be quantified and studied ...
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