A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes,Kevin Yang,Kyle Swanson,Wengong Jin,Andres Cubillos-Ruiz,Nina M. Donghia,Craig R. MacNair,Shawn French,Lindsey A. Carfrae,Zohar Bloom-Ackermann,Victoria M. Tran,Anush Chiappino-Pepe,Ahmed H. Badran,Ian W. Andrews,Ian W. Andrews,Ian W. Andrews,Emma J. Chory,George M. Church,Eric D. Brown,Tommi S. Jaakkola,Regina Barzilay,James J. Collins +21 more
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TLDR
A deep neural network capable of predicting molecules with antibacterial activity is trained and a molecule from the Drug Repurposing Hub-halicin- is discovered that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens.About:
This article is published in Cell.The article was published on 2020-02-20 and is currently open access. It has received 1002 citations till now.read more
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Journal ArticleDOI
Native-resolution myocardial principal Eulerian strain mapping using convolutional neural networks and Tagged Magnetic Resonance Imaging.
Inas A. Yassine,Ahmed M. Ghanem,Nader S. Metwalli,Ahmed Hamimi,Ronald Ouwerkerk,Jatin R. Matta,Michael A. Solomon,Jason M. Elinoff,Ahmed M. Gharib,Khaled Z. Abd-Elmoniem +9 more
TL;DR: In this article, the authors compute myocardial principal strain maps e p 1 and e p 2 from tagged MRI (tMRI) at the native image resolution using deep-learning local patch convolutional neural network (CNN) models (DeepStrain).
Journal ArticleDOI
Quantitative Prediction of Inorganic Nanomaterial Cellular Toxicity via Machine Learning.
Nikolai Shirokii,Yevgeniya Din,Ilia A. Petrov,Yu. M. Seregin,Sofia Sirotenko,Julia Razlivina,Nikita S. Serov,Vladimir Vinogradov +7 more
TL;DR: In this paper , an ML-based approach is proposed to the quantitative prediction of inorganic nanomaterial cytotoxicity achieving the precision expressed by 10-fold cross-validation (CV) Q2 ǫ 0.86 with the root mean squared error (RMSE) of 12.2% obtained by the correlation-based feature selection and grid search-based model hyperparameters optimization.
Peer ReviewDOI
Super-Resolution Optical Imaging of Bacterial Cells
TL;DR: A review of different super-resolution microscopy approaches used by microbiologists to investigate bacterial cell morphology and functions is presented in this paper , where the resolution achieved and focus on fluorophore selection and other critical imaging requirements.
Journal ArticleDOI
In Vitro Activity of a Novel Siderophore-Cephalosporin LCB10-0200 (GT-1), and LCB10-0200/Avibactam, against Carbapenem-Resistant Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa Strains at a Tertiary Hospital in Korea
Le Phuong Nguyen,Chul Soon Park,Naina Adren Pinto,Hyun-Sook Lee,Hyun Soo Seo,Thao Nguyen Vu,Hung Mai,An H.T. Pham,Eris Jang,Young Lag Cho,Karrie Goglin,Kevin Nguyen,Richard C. White,Roshan D'Souza,Derrick E. Fouts,Dongeun Yong +15 more
TL;DR: The siderophore-antibiotic conjugate LCB10-0200 (a.k.a. GT-1) has been developed to combat multidrug-resistant Gram-negative bacteria as mentioned in this paper.
Journal ArticleDOI
Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries
TL;DR: This paper presented an end-to-end Bayesian language model-based method for designing large and diverse libraries of high-affinity single-chain variable fragments (scFvs) that are then empirically measured.
References
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