Results 51 to 60 of about 3,260,181 (300)

On computing least order fault detectors using rational nullspace bases [PDF]

, 2003
We propose a numerically reliable computational approach to design least order fault detectors using descriptor system techniques. This approach is based on a new numerically stable algorithm to compute least order rational nullspace bases of rational ...
A. Varga, Varga, Andras
core   +1 more source

Machine learning prediction on intermetallic compounds with implemented virtual-center-atom structural descriptor

Science and Technology of Advanced Materials: Methods, 2022
A virtual-center-atom (VCA) structural descriptor was proposed to construct machine learning potentials which can be applied in studying alloy materials.
Zhenwei Li, Junjie Wang
doaj   +1 more source

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 more
wiley   +1 more source

Mining Structural Information from Gas Chromatography-Electron-Impact Ionization-Mass Spectrometry Data for Analytical-Descriptor-Based Quantitative Structure–Activity Relationship

Journal of Xenobiotics
Recently developed quantitative structure–activity relationship (QSAR) prediction uses machine learning techniques with analytical signals from the full scan of mass spectra as input, and does not need exhaustive structural determination to assess ...
Yasuyuki Zushi
doaj   +1 more source

QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors [PDF]

Journal of Chemistry Letters
This study presents a computational approach for designing potent compounds against breast cancer. A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts ...
Auwal Isa, Adamu Uzairu, umar Umar, Muhammad Tukur Ibrahim, Abdullahi Umar   +4 more
doaj   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Local Descriptor Revision

, 2017
In this chapter the properties of descriptor revision, as defined in Chapter 4, are further explored. Several alternative selection mechanisms are presented, and the properties of the resulting operations are investigated.
Sven Ove Hansson, Hansson, Sven Ove,
core   +1 more source

The planar cell polarity protein Vangl2 interacts with the PDZ‐domains of Scribble but not with a unique PDZ‐like domain in Inturned

FEBS Letters, EarlyView.
Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes, Jan Brysch, Carmen Gelze, Lilli Meier, Daniel Kümmel   +4 more
wiley   +1 more source

E_min: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability [PDF]

Predicting the synthesizability of a new molecule remains an unsolved challenge that chemists have long tackled with heuristic approaches. Here, we report a new method for predicting synthesizability using a simple, yet accurate thermochemical descriptor.
Hassan, Harb, Rajeev S., Assary, Logan, Ward, Andrew, Lee, Larry A., Curtiss, Ian T., Foster, Sarah N., Elliott   +6 more
core   +1 more source

CathepsinDL: Deep Learning-Driven Model for Cathepsin Inhibitor Screening and Drug Target Identification

IEEE Access
Cathepsins are lysosomal proteases which are crucial for protein breakdown, bone remodelling and antigen processing and whose dysregulation leads to diseases like cancer, osteoporosis and neurodegenerative disorders, making them an important drug target.
Mohammed Junaid Anwar Qader, Chandra Mohan Sah, Tapan Kumar Sahoo, Santosh Kumar Majhi, Kaushik Mishra   +4 more
doaj   +1 more source