11 papers · ranked by Valyu relevance
Martin Seifrid, Stanley Lo, Dylan Choi, Gary Tom + 12 more
Martin Seifrid 1 , Stanley Lo 2 , Dylan G. Choi 3 , Gary Tom 2 , My Linh Le 3 , Kunyu Li 3 , Rahul Sankar 3 , Hoai-Thanh Vuong 3 , Hiba Wakidi 3 , Ahra Yi 3 , Ziyue Zhu 3 , Nora Schopp 3 , Aaron Peng 3 , Benjamin Luginbuhl 3 , Thuc-Quyen Nguyen 3 , Alán Aspuru-Guzik 2
Diba Behnoudfar, Cory Simon, Joshua Schrier
Aqueous, two-phase systems (ATPSs) may form upon mixing two solutions of independently water-soluble compounds. Many separation, purification, and extraction processes rely on ATPSs. Predicting the miscibility of solutions can accelerate and reduce the cost of the discovery of new ATPSs for these applications. Whereas…
Authors not listed
Chemical data is fundamentally sparse, with molecular structures serving as database keys for countless properties. Current machine learning methods map structures to properties with remarkable accuracy, yet they do not leverage available property information when predicting unknowns, creating unutilized partial…
Bartłomiej Fliszkiewicz, Marcin Sajdak
The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended databases. A number of compounds with results from quantum-chemical…
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Solute carrier (SLC) transporters constitute the largest family of membrane transport proteins in humans. They facilitate the movement of ions, neurotransmitters, nutrients, and drugs. Given their critical role in regulating cellular physiology, they are important therapeutic targets for neurological and psychological…
Sangjoon Lee, Clio Chen, Griheydi Garcia, Anton Oliynyk
Materials informatics uses data-driven approaches for the study and discovery of materials. Features or descriptors are the crucial components in generating reliable and accurate machine-learning models. While general data can be acquired through public and commercial sources, features must be tailored for a specific…
Chonghuan Zhang, Adarsh Arun, Alexei Lapkin
Computer Aided Synthesis Planning (CASP) development of reaction routes requires understanding of complete reaction structures. However, most reactions in the current databases are missing reaction co-participants. Although reaction prediction and atom mapping tools can predict major reaction participants and trace…
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The precision of thermodynamic modeling for ionic liquid (IL)–solute systems is fundamentally reliant on the quality of experimental data. However, prevalent databases such as ILThermo frequently exhibit conflicting measurements for the same systems under identical temperature and pressure conditions. These disparities…
David Buterez, Jon Paul Janet, Steven Kiddle, Pietro Liò
High throughput screening (HTS) is one of the leading techniques for hit identification in drug discovery and comprises of multiple phases, one primary and one or more confirmatory screens which result in multi-fidelity data. Noisy primary screening data are available on a large number of compounds and higher quality…
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Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi + 1 more
Materials informatics and cheminformatics struggle with data scarcity, hindering the extraction of significant relationships between structures and properties. The "Ugly Duckling" theorem, suggesting the difficulty of data processing without assumptions or prior knowledge, exacerbates this problem. Current…