Results 21 to 30 of about 30,351 (277)

ChemTSv2: Democratizing Functional Molecular Design Using de novo Molecule Generator

, 2023
Designing functional molecules is the prerogative of experts who have advanced knowledge and experience in their fields. To democratize automatic molecular design for both experts and non-experts, we introduce a generic open-sourced framework, ChemTSv2 ...
Koji, Tsuda, Tatsuya, Yoshizawa, Shoichi, Ishida, Tanuj, Aasawat, Kazuki, Yoshizoe, Masato, Sumita, Kei, Terayama, Michio, Katouda   +7 more
core   +1 more source

COMA: efficient structure-constrained molecular generation using contractive and margin losses

Journal of Cheminformatics, 2023
Background Structure-constrained molecular generation is a promising approach to drug discovery. The goal of structure-constrained molecular generation is to produce a novel molecule that is similar to a given source molecule (e.g. hit molecules) but has
Jonghwan Choi, Sangmin Seo, Sanghyun Park   +2 more
doaj   +1 more source

MORTAR: a rich client application for in silico molecule fragmentation

Journal of Cheminformatics, 2023
Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process.
Felix Bänsch, Jonas Schaub, Betül Sevindik, Samuel Behr, Julian Zander, Christoph Steinbeck, Achim Zielesny   +6 more
doaj   +1 more source

Expanding the use of ethanol as a feedstock for cell-free synthetic biochemistry by implementing acetyl-CoA and ATP generating pathways

Scientific Reports, 2022
Ethanol is a widely available carbon compound that can be increasingly produced with a net negative carbon balance. Carbon-negative ethanol might therefore provide a feedstock for building a wider range of sustainable chemicals.
Hongjiang Liu, Mark A. Arbing, James U. Bowie   +2 more
doaj   +1 more source

Powerful molecule generation with simple ConvNet

Bioinformatics, 2022
AbstractMotivationAutomated molecule generation is a crucial step in in-silico drug discovery. Graph-based generation algorithms have seen significant progress over recent years. However, they are often complex to implement, hard to train and can under-perform when generating long-sequence molecules. The development of a simple and powerful alternative
Hongyang K Yu, Hongjiang C Yu
openaire   +2 more sources

Learned Feature Generation for Molecules [PDF]

, 2018
When classifying molecules for virtual screening, the molecular structure first needs to be converted into meaningful features, before a classifier can be trained. The most common methods use a static algorithm that has been created based on domain knowledge to perform this generation of features. We propose an approach where this conversion is learned
Winter, Patrick, Borgelt, Christian, Berthold, Michael R.   +2 more
openaire   +2 more sources

In-situ electro-responsive through-space coupling enabling foldamers as volatile memory elements

Nature Communications, 2023
Voltage-gated processing units are fundamental components for non-von Neumann architectures like memristor and electric synapses, on which nanoscale molecular electronics have possessed great potentials.
Jinshi Li, Pingchuan Shen, Zeyan Zhuang, Junqi Wu, Ben Zhong Tang, Zujin Zhao   +5 more
doaj   +1 more source

Measuring Intracellular H2O2 in Intact Human Cells Using the Genetically Encoded Fluorescent Sensor HyPer7

Bio-Protocol, 2022
Depending on its local concentration, hydrogen peroxide (H2O2) can serve as a cellular signaling molecule but can also cause damage to biomolecules.
Lianne Jacobs, Michaela Hoehne, Jan Riemer   +2 more
doaj   +1 more source

Equivariant Diffusion for Molecule Generation in 3D

CoRR, 2022
Accepted at International Conference on Machine Learning (ICML ...
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling   +3 more
openaire   +3 more sources

Diversity oriented Deep Reinforcement Learning for targeted molecule generation

Journal of Cheminformatics, 2021
In this work, we explore the potential of deep learning to streamline the process of identifying new potential drugs through the computational generation of molecules with interesting biological properties.
Tiago Pereira, Maryam Abbasi, Bernardete Ribeiro, Joel P. Arrais   +3 more
doaj   +1 more source