Search
Search Results
-
Landscape classification with self-organizing map using user participation and environmental data: the case of the Seoul Metropolitan Area
This study aimed to develop a method for assessing landscapes using environmental data and user-generated data, which are commonly employed in...
-
Diversity, structure, and application of self organizing map on plant species in homegardens
The high diversity of plant species in homegardens contributes to the provision of a range of goods and services, as well as considerably benefiting...
-
Colour sorting of red oak, yellow poplar and maple veneers using self-organizing map: comparisons between different camera genres
Colour sorting is a vital process in manufacturing of high-quality wood products. It is however a manual process in a large majority of manufacturing...
-
Identification of environment types and adaptation zones with self-organizing maps; applications to sunflower multi-environment data in Europe
Key messageWe evaluate self-organizing maps (SOM) to identify adaptation zones and visualize multi-environment genotypic responses. We apply SOM to...
-
Analysis of the uncharted, druglike property space by self-organizing maps
Physicochemical properties are fundamental to predict the pharmacokinetic and pharmacodynamic behavior of drug candidates. Easily calculated...
-
Self-organizing maps with variable neighborhoods facilitate learning of chromatin accessibility signal shapes associated with regulatory elements
BackgroundAssigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of...
-
Self-organizing maps: a powerful tool for capturing genetic diversity patterns of populations
The maintenance of genetic diversity is fundamental to ensure the population’s viability and to perceive how the evolutionary factors act on these....
-
Moderate protein intake percentage in mice for maintaining metabolic health during approach to old age
Nutritional requirements for maintaining metabolic health may vary with each life stage, such as young, middle, and old age. To investigate the...
-
Assessing and Predicting Soil Quality in Heavy Metal-Contaminated Soils: Statistical and ANN-Based Techniques
This study aimed to evaluate the pollution status of soils contaminated with heavy metals using different statistical techniques and artificial...
-
Genetic patterns recognition in crop species using self-organizing map: the example of the highly heterozygous autotetraploid potato (Solanum tuberosum L.)
We tested the ability of the self-organizing map (SOM), a type of artificial neural network, in revealing genetic patterns within the autotetraploid...
-
Bioregionalization of Albania: Mismatch between the flora and the climate suggests that our models of Southern European bioregions are in need of a revision
We analysed the floristic subdivisions of Albania by hierarchical clustering of all the vascular plant species of Albania over a grid of 25 km cells,...
-
Asclepiadoideae subfamily (Apocynaceae): ethnopharmacology, biological activities and chemophenetics based on pregnane glycosides
Apocynaceae, one of the largest plant families with over 5.100 widely distributed species, serves as a significant model for evolutionary and...
-
eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells
BackgroundBioinformatics capability to analyze spatio–temporal dynamics of gene expression is essential in understanding animal development. Animal...
-
Envirotype approach for soybean genotype selection through the integration of georeferenced climate and genetic data using artificial neural networks
The selection of better-evaluated genotypes for a target region depends on the characterization of the climate conditions of the environment. With...
-
Cross-grain fracture characterization in softwood using artificial neural network analysis of acoustic emissions
In an effort to better understand crack growth in the cross-grain direction, an acoustic emission (AE) approach was implemented to monitor the...
-
CircTHBS1 drives gastric cancer progression by increasing INHBA mRNA expression and stability in a ceRNA- and RBP-dependent manner
Circular RNAs (circRNAs) play vital regulatory roles in the progression of multiple cancers. In our study, transcriptome analysis and self-organizing...
-
Comparative genomic analysis of the human genome and six bat genomes using unsupervised machine learning: Mb-level CpG and TFBS islands
BackgroundEmerging infectious disease-causing RNA viruses, such as the SARS-CoV-2 and Ebola viruses, are thought to rely on bats as natural reservoir...
-
Building 2D classification models and 3D CoMSIA models on small-molecule inhibitors of both wild-type and T790M/L858R double-mutant EGFR
AbstractEpidermal growth factor receptor (EGFR) has received widespread attention because it is an important target for anticancer drug design....
-
Classification models and SAR analysis on HDAC1 inhibitors using machine learning methods
Histone deacetylase (HDAC) 1, a member of the histone deacetylases family, plays a pivotal role in various tumors. In this study, we collected 7313...
-
Detecting the attack of the fall armyworm (Spodoptera frugiperda) in cotton plants with machine learning and spectral measurements
The Spodoptera frugiperda (i.e., fall armyworm) causes irreversible damage in cotton cultivars, and its visual inspection on plants is a burdensome...
