AIMC Topic: Biological Products
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Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.
Biomolecules
Sep 28, 2020
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...
Privileged Scaffold Analysis of Natural Products with Deep Learning-based Indication Prediction Model.
Molecular informatics
May 14, 2020
Natural products play a vital role in the drug discovery and development process as an important source of reliable and novel lead structures. But the existing criteria for drug leads were usually developed for synthetic compounds and cannot be direc...
The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics.
BMC medical genomics
Apr 3, 2020
In this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9-11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this suppl...
A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products.
Journal of the American Chemical Society
Feb 21, 2020
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...
Predicting the Associations between Meridians and Chinese Traditional Medicine Using a Cost-Sensitive Graph Convolutional Neural Network.
International journal of environmental research and public health
Jan 23, 2020
Natural products are the most important and commonly used in Traditional Chinese Medicine (TCM) for healthcare and disease prevention in East-Asia. Although the Meridian system of TCM was established several thousand years ago, the rationale of Merid...
Application of a kNN-based similarity method to biopharmaceutical manufacturing.
Biotechnology progress
Dec 16, 2019
Machine learning-based similarity analysis is commonly found in many artificial intelligence applications like the one utilized in e-commerce and digital marketing. In this study, a kNN-based (k-nearest neighbors) similarity method is proposed for ra...
The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.
Arthritis research & therapy
Nov 9, 2019
BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory biomarkers of remission are still lacking. In this study, we used machine learning to predict JIA activ...
Antitubercular metabolites from the marine-derived fungus strain MF029.
Natural product research
Sep 6, 2019
During the systematic screening of bioactive compounds from our marine natural product library, crude extract of the marine-derived fungus strain MF029 exhibited moderate bioactivities against , S, methicillin-resistant , and bacillus Calmette-Guér...
Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.
ChemMedChem
May 16, 2019
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...
Large-Scale Screening of Natural Products Transactivating Peroxisome Proliferator-Activated Receptor α Identifies 9S-Hydroxy-10E,12Z,15Z-Octadecatrienoic Acid and Cymarin as Potential Compounds Capable of Increasing Apolipoprotein A-I Transcription in Human Liver Cells.
Lipids
Feb 1, 2019
Increasing apolipoprotein A-I (apoA-I), the predominant protein of high-density lipoprotein (HDL) particles, has favorable effects on atherogenic risk factors. Here, we investigated the effects of peroxisome proliferator-activated receptor α (PPARα) ...
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