Zobrazeno 1 - 10
of 1 940
pro vyhledávání: '"Tropsha, A."'
Autor:
Olasunkanmi, Olawumi, Morris, Evan, Kebede, Yaphet, Lee, Harlin, Ahalt, Stanley, Tropsha, Alexander, Bizon, Chris
Knowledge graphs (KGs) represent connections and relationships between real-world entities. We propose a link prediction framework for KGs named Enrichment-Driven GrAph Reasoner (EDGAR), which infers new edges by mining entity-local rules. This appro
Externí odkaz:
http://arxiv.org/abs/2409.18659
Expansive Matching of Experts (EMOE) is a novel method that utilizes support-expanding, extrapolatory pseudo-labeling to improve prediction and uncertainty based rejection on out-of-distribution (OOD) points. We propose an expansive data augmentation
Externí odkaz:
http://arxiv.org/abs/2406.01825
Structure-based virtual screening (SBVS) is a key workflow in computational drug discovery. SBVS models are assessed by measuring the enrichment of known active molecules over decoys in retrospective screens. However, the standard formula for enrichm
Externí odkaz:
http://arxiv.org/abs/2403.10478
Autor:
Kirchoff, Kathryn E., Wellnitz, James, Hochuli, Joshua E., Maxfield, Travis, Popov, Konstantin I., Gomez, Shawn, Tropsha, Alexander
Nearest neighbor-based similarity searching is a common task in chemistry, with notable use cases in drug discovery. Yet, some of the most commonly used approaches for this task still leverage a brute-force approach. In practice this can be computati
Externí odkaz:
http://arxiv.org/abs/2402.07970
In deep learning for drug discovery, chemical data are often represented as simplified molecular-input line-entry system (SMILES) sequences which allow for straightforward implementation of natural language processing methodologies, one being the seq
Externí odkaz:
http://arxiv.org/abs/2310.02744
Autor:
Maxfield, Travis, Hochuli, Joshua, Wellnitz, James, Melo-Filho, Cleber, Popov, Konstantin I., Muratov, Eugene, Tropsha, Alex
Modeling the properties of chemical mixtures is a difficult but important part of any modeling process intended to be applicable to the often messy and impure phenomena of everyday life, including food and environmental safety, healthcare, etc. Part
Externí odkaz:
http://arxiv.org/abs/2308.06347
Molecular docking aims to predict the 3D pose of a small molecule in a protein binding site. Traditional docking methods predict ligand poses by minimizing a physics-inspired scoring function. Recently, a diffusion model has been proposed that iterat
Externí odkaz:
http://arxiv.org/abs/2307.12090
Autor:
Kristina Edfeldt, Aled M. Edwards, Ola Engkvist, Judith Günther, Matthew Hartley, David G. Hulcoop, Andrew R. Leach, Brian D. Marsden, Amelie Menge, Leonie Misquitta, Susanne Müller, Dafydd R. Owen, Kristof T. Schütt, Nicholas Skelton, Andreas Steffen, Alexander Tropsha, Erik Vernet, Yanli Wang, James Wellnitz, Timothy M. Willson, Djork-Arné Clevert, Benjamin Haibe-Kains, Lovisa Holmberg Schiavone, Matthieu Schapira
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract The Structural Genomics Consortium is an international open science research organization with a focus on accelerating early-stage drug discovery, namely hit discovery and optimization. We, as many others, believe that artificial intelligenc
Externí odkaz:
https://doaj.org/article/d7b4037ed6df47b49327448e7112d3fb
Autor:
Karla Gonzalez-Ponce, Carolina Horta Andrade, Fiona Hunter, Johannes Kirchmair, Karina Martinez-Mayorga, José L. Medina-Franco, Matthias Rarey, Alexander Tropsha, Alexandre Varnek, Barbara Zdrazil
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-8 (2023)
Abstract We report the major highlights of the School of Cheminformatics in Latin America, Mexico City, November 24–25, 2022. Six lectures, one workshop, and one roundtable with four editors were presented during an online public event with speaker
Externí odkaz:
https://doaj.org/article/c9a69d2acfea4f7f825f83006b877516
Publikováno v:
npj Vaccines, Vol 8, Iss 1, Pp 1-15 (2023)
Abstract COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women
Externí odkaz:
https://doaj.org/article/22fcaec77d4a41caa482049a41f886d0