Large sets of endomorphisms and of g-measures

1978 ◽  
pp. 191-210 ◽  
Author(s):  
Marion Rachel Palmer ◽  
William Parry ◽  
Peter Walters
Keyword(s):  
Large Sets

Large sets of Kirkman triple systems of orders 22n+1+1

2021 ◽  
Vol 344 (6) ◽  
pp. 112373
Author(s):  
Juanjuan Xu ◽  
Lijun Ji
Keyword(s):  
Triple Systems ◽  
Large Sets

scholarly journals BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space

2021 ◽  
Vol 22 (15) ◽  
pp. 7773
Author(s):  
Neann Mathai ◽  
Conrad Stork ◽  
Johannes Kirchmair
Keyword(s):  
Large Scale ◽  
Computational Approach ◽  
Large Sets ◽  
Compound Libraries ◽  
Wide Range ◽  
Protein Space ◽  
High Chance ◽  
Large Scale Screening ◽  
Early Drug ◽  
Selection Of

Experimental screening of large sets of compounds against macromolecular targets is a key strategy to identify novel bioactivities. However, large-scale screening requires substantial experimental resources and is time-consuming and challenging. Therefore, small to medium-sized compound libraries with a high chance of producing genuine hits on an arbitrary protein of interest would be of great value to fields related to early drug discovery, in particular biochemical and cell research. Here, we present a computational approach that incorporates drug-likeness, predicted bioactivities, biological space coverage, and target novelty, to generate optimized compound libraries with maximized chances of producing genuine hits for a wide range of proteins. The computational approach evaluates drug-likeness with a set of established rules, predicts bioactivities with a validated, similarity-based approach, and optimizes the composition of small sets of compounds towards maximum target coverage and novelty. We found that, in comparison to the random selection of compounds for a library, our approach generates substantially improved compound sets. Quantified as the “fitness” of compound libraries, the calculated improvements ranged from +60% (for a library of 15,000 compounds) to +184% (for a library of 1000 compounds). The best of the optimized compound libraries prepared in this work are available for download as a dataset bundle (“BonMOLière”).

The existence of r-large sets of Mendelsohn triple systems

2021 ◽  
Vol 344 (8) ◽  
pp. 112444
Author(s):  
Xiangqian Li ◽  
Yanxun Chang ◽  
Zihong Tian
Keyword(s):  
Triple Systems ◽  
Large Sets

Further results on large sets of partitioned incomplete Latin squares

2021 ◽  
Author(s):  
Cong Shen ◽  
Dongliang Li ◽  
Haitao Cao
Keyword(s):  
Latin Squares ◽  
Large Sets

scholarly journals Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification

2021 ◽  
Vol 18 (11) ◽  
pp. 6099
Author(s):  
Joel Weijia Lai ◽  
Candice Ke En Ang ◽  
U. Rajendra Acharya ◽  
Kang Hao Cheong
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Daily Living ◽  
Learning Algorithms ◽  
Health Condition ◽  
Machine Learning Algorithms ◽  
Human Cognition ◽  
Computer Algorithms ◽  
Large Sets ◽  
Prevention Methods

Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software with allowable thresholds to make deterministic approximate conclusions. In comparison to traditional technologies in healthcare, artificial intelligence enhances the process of data analysis without the need for human input, producing nearly equally reliable, well defined output. Schizophrenia is a chronic mental health condition that affects millions worldwide, with impairment in thinking and behaviour that may be significantly disabling to daily living. Multiple artificial intelligence and machine learning algorithms have been utilized to analyze the different components of schizophrenia, such as in prediction of disease, and assessment of current prevention methods. These are carried out in hope of assisting with diagnosis and provision of viable options for individuals affected. In this paper, we review the progress of the use of artificial intelligence in schizophrenia.

scholarly journals Bohr Sets in Triple Products of Large Sets in Amenable Groups

2018 ◽  
Vol 25 (3) ◽  
pp. 923-936
Author(s):  
Michael Björklund ◽  
John T. Griesmer
Keyword(s):  
Amenable Groups ◽  
Large Sets
Sign in / Sign up

Export Citation Format

Share Document