Results 121 to 130 of about 6,104,936 (275)

Geometric deep learning for molecular property predictions with chemical accuracy across chemical space

Journal of Cheminformatics
Chemical engineers heavily rely on precise knowledge of physicochemical properties to model chemical processes. Despite the growing popularity of deep learning, it is only rarely applied for property prediction due to data scarcity and limited accuracy ...
Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem   +3 more
doaj   +1 more source

The property market in China

, 2001
Since the new land tenure system, known as the Land Use Rights system (LUR), was introduced in 1978, there has been significant development in the Chinese property market.
Chan, Nelson, Jia, Shi-Jun
core  

Contrastive Dual-Interaction Graph Neural Network for Molecular Property Prediction

Molecular property prediction is a key component of AI-driven drug discovery and molecular characterization learning. Despite recent advances, existing methods still face challenges such as limited ability to generalize, and inadequate representation of ...
Wu, Xiaopeng, Li, Fuyi, Gao, Xiaojun, Zhao, Zexing, Ren, Ruohua, Shi, Guangsi   +5 more
core   +1 more source

Chemi-Net: A Molecular Graph Convolutional Network for Accurate Drug Property Prediction

, 2019
Absorption, distribution, metabolism, and excretion (ADME) studies are critical for drug discovery. Conventionally, these tasks, together with other chemical property predictions, rely on domain-specific feature descriptors, or fingerprints.
Xiangyan Sun, Jie Fan, Junqiu Wu, Hua Gao, Yax Sun, Florian Boulnois, Ke Liu, Lei Jia, Jun Ma, Haoming Xing   +9 more
core   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules

npj Computational Materials
Discovery of high-performance materials and molecules requires identifying extremes with property values that fall outside the known distribution. Therefore, the ability to extrapolate to out-of-distribution (OOD) property values is critical for both ...
Nofit Segal, Aviv Netanyahu, Kevin P. Greenman, Pulkit Agrawal, Rafael Gómez-Bombarelli   +4 more
doaj   +1 more source

Molecular property prediction: Input types and information processing in machine learning models

Results in Engineering
Molecular property prediction is at the core of machine learning (ML)-driven materials and drug discovery. Effectively navigating the ML workflow requires careful consideration of molecular representations, input preparation strategies, and model ...
Muhammed Thameem, Obaid AlHmoudi, Ahmad Al Salloum, Naeema Al Darmaki, Ali Elkamel, Ali A. AlHammadi   +5 more
doaj   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

Molecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq, Marc Terrones, Felicia Rodrigues Fortes, Anne Schepers, Alessia Denis, Christophe Deben, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer   +8 more
wiley   +1 more source

VAE-Assisted Data Augmentation for Improved Molecular Prediction with Graph Neural Networks (GNNs) in Low-Data Regimes

Chemical Engineering Transactions
This study presents a novel approach to enhancing molecular property prediction through variational autoencoder (VAE)-assisted data augmentation in low-data regimes.
Gabriela C. Theis Marchan, Pegah Naghshnejad, Andrew Okafor, Jose A. Romagnoli   +3 more
doaj