From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Computer-Aided Molecular Design"
DOI: 10.1007/s10822-024-00555-3
Abstract: Scaffold replacement as part of an optimization process that requires maintenance of potency, desirable biodistribution, metabolic stability, and considerations of synthesis at very large scale is a complex challenge. Here, we consider a set of… read more here.
Keywords: macrocyclic natural; natural product; active learning; learning identify ... See more keywords
Learning to Identify Physiological and Adventitious Metal-Binding Sites in the Three-Dimensional Structures of Proteins by Following the Hints of a Deep Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.2c00522
Abstract: Thirty-eight percent of protein structures in the Protein Data Bank contain at least one metal ion. However, not all these metal sites are biologically relevant. Cations present as impurities during sample preparation or in the… read more here.
Keywords: network; physiological adventitious; learning identify; metal ... See more keywords
Unsupervised Deep Learning Can Identify Protein Functional Groups from Unaligned Sequences
Sign Up to like & getrecommendations! Published in 2023 at "Genome Biology and Evolution"
DOI: 10.1093/gbe/evad084
Abstract: Abstract Interpreting protein function from sequence data is a fundamental goal of bioinformatics. However, our current understanding of protein diversity is bottlenecked by the fact that most proteins have only been functionally validated in model… read more here.
Keywords: unsupervised deep; learning identify; learning; deep learning ... See more keywords
Abstract 13102: Prediction of Incident AF With Deep Learning Can Identify Patients at High Risk for AF-related Stroke
Sign Up to like & getrecommendations! Published in 2020 at "Circulation"
DOI: 10.1161/circ.142.suppl_3.13102
Abstract: Background: Atrial fibrillation (AF) is associated with stroke, especially when AF goes undetected. Deep neural networks (DNN) can predict incident AF from a 12-lead resting ECG. We hypothesize tha... read more here.
Keywords: 13102 prediction; abstract 13102; learning identify; incident deep ... See more keywords
Use of machine learning to identify functional connectivity changes in a clinical cohort of patients at risk for dementia
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Aging Neuroscience"
DOI: 10.3389/fnagi.2022.962319
Abstract: Objective Progressive conditions characterized by cognitive decline, including mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are clinical conditions representing a major risk factor to develop dementia, however, the diagnosis of these pre-dementia conditions… read more here.
Keywords: use machine; learning identify; machine learning; neuropsychological tests ... See more keywords