Zobrazeno 1 - 10
of 129
pro vyhledávání: '"Aldeghi, Matteo"'
Autor:
Aldeghi, Matteo, Graff, David E., Frey, Nathan, Morrone, Joseph A., Pyzer-Knapp, Edward O., Jordan, Kirk E., Coley, Connor W.
Publikováno v:
J. Chem. Inf. Model. 2022, 62, 19, 4660-4671
In molecular discovery and drug design, structure-property relationships and activity landscapes are often qualitatively or quantitatively analyzed to guide the navigation of chemical space. The roughness (or smoothness) of these molecular property l
Externí odkaz:
http://arxiv.org/abs/2207.09250
Autor:
Aldeghi, Matteo, Coley, Connor W.
Publikováno v:
Chem. Sci., 2022,13, 10486-10498
Synthetic polymers are versatile and widely used materials. Similar to small organic molecules, a large chemical space of such materials is hypothetically accessible. Computational property prediction and virtual screening can accelerate polymer desi
Externí odkaz:
http://arxiv.org/abs/2205.08619
Autor:
Graff, David E., Aldeghi, Matteo, Morrone, Joseph A., Jordan, Kirk E., Pyzer-Knapp, Edward O., Coley, Connor W.
High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules. In cases where the library of molecules is exceedingly large, the cost of an exhaustive virtual screen may be prohibitive. Model-guided opti
Externí odkaz:
http://arxiv.org/abs/2205.01753
Autor:
Krenn, Mario, Pollice, Robert, Guo, Si Yue, Aldeghi, Matteo, Cervera-Lierta, Alba, Friederich, Pascal, Gomes, Gabriel dos Passos, Häse, Florian, Jinich, Adrian, Nigam, AkshatKumar, Yao, Zhenpeng, Aspuru-Guzik, Alán
Publikováno v:
Nature Review Physics 4, 761 (2022)
Imagine an oracle that correctly predicts the outcome of every particle physics experiment, the products of every chemical reaction, or the function of every protein. Such an oracle would revolutionize science and technology as we know them. However,
Externí odkaz:
http://arxiv.org/abs/2204.01467
Publikováno v:
Digital Discovery, 2022,1, 732-744
Optimization strategies driven by machine learning, such as Bayesian optimization, are being explored across experimental sciences as an efficient alternative to traditional design of experiment. When combined with automated laboratory hardware and h
Externí odkaz:
http://arxiv.org/abs/2203.17241
Publikováno v:
Chemical Science, 2021, 12, 14792 - 14807
Numerous challenges in science and engineering can be framed as optimization tasks, including the maximization of reaction yields, the optimization of molecular and materials properties, and the fine-tuning of automated hardware protocols. Design of
Externí odkaz:
http://arxiv.org/abs/2103.03716
Autor:
Nigam, AkshatKumar, Pollice, Robert, Hurley, Matthew F. D., Hickman, Riley J., Aldeghi, Matteo, Yoshikawa, Naruki, Chithrananda, Seyone, Voelz, Vincent A., Aspuru-Guzik, Alán
Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and drug design. Recently, machine learning techniques have emerged as a powerful and cost-eff
Externí odkaz:
http://arxiv.org/abs/2102.11439
Autor:
Häse, Florian, Aldeghi, Matteo, Hickman, Riley J., Roch, Loïc M., Christensen, Melodie, Liles, Elena, Hein, Jason E., Aspuru-Guzik, Alán
Publikováno v:
Mach. Learn.: Sci. Technol. 2 (2021) 035021
Research challenges encountered across science, engineering, and economics can frequently be formulated as optimization tasks. In chemistry and materials science, recent growth in laboratory digitization and automation has sparked interest in optimiz
Externí odkaz:
http://arxiv.org/abs/2010.04153
Publikováno v:
Appl. Phys. Rev. 8 (2021) 031406
Designing functional molecules and advanced materials requires complex design choices: tuning continuous process parameters such as temperatures or flow rates, while simultaneously selecting catalysts or solvents. To date, the development of data-dri
Externí odkaz:
http://arxiv.org/abs/2003.12127
Autor:
Aldeghi, Matteo
Computer simulations of biomolecules have been improving at a pace that is faster than Moore's law for microprocessors in the last few decades. Thanks to advances in theory, hardware, and algorithms it is increasingly possible to study biological pro
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730278