Results 11 to 20 of about 25,449,411 (299)

Predictive design of sigma factor-specific promoters

Nature Communications, 2020
Automated design tools and tailored subunits are beneficial in fine-tuning all components of a complex genetic circuit. Here the authors create E. coli and B.
Maarten Van Brempt, Jim Clauwaert, Friederike Mey, Michiel Stock, Jo Maertens, Willem Waegeman, Marjan De Mey   +6 more
doaj   +1 more source

An Adaptive Large Neighborhood Search for the Larger-Scale Instances of Green Vehicle Routing Problem with Time Windows

Complexity, 2020
Due to huge amount of greenhouse gases emission (such as CO2), freight has been adversely affecting the global environment in facilitating the global economy.
Zixuan Yu, Ping Zhang, Yang Yu, Wei Sun, Min Huang   +4 more
doaj   +1 more source

A neural network‐based framework to understand the type 2 diabetes‐related alteration of the human gut microbiome

iMeta, 2022
The identification of microbial markers adequate to delineate the disease‐related microbiome alterations from the complex human gut microbiota is of great interest.
Shun Guo, Haoran Zhang, Yunmeng Chu, Qingshan Jiang, Yingfei Ma   +4 more
doaj   +1 more source

Synthetic Data Generation for Data Envelopment Analysis

Data, 2023
The paper is devoted to the problem of generating artificial datasets for data envelopment analysis (DEA), which can be used for testing DEA models and methods.
Andrey V. Lychev
doaj   +1 more source

Synthetic Data for Feature Selection

, 2023
Feature selection is an important and active field of research in machine learning and data science. Our goal in this paper is to propose a collection of synthetic datasets that can be used as a common reference point for feature selection algorithms.
Firuz Kamalov, Hana Sulieman, Aswani Kumar Cherukuri   +2 more
openaire   +4 more sources

Predicting the frequencies of drug side effects

Nature Communications, 2020
Currently, the frequencies of drug side effects are determined in randomised controlled clinical trials. Here the authors develop an interpretable machine learning approach to predict the frequencies of unknown side effects for drugs with a small number ...
Diego Galeano, Shantao Li, Mark Gerstein, Alberto Paccanaro   +3 more
doaj   +1 more source

An Adversary Model of Fraudsters’ Behavior to Improve Oversampling in Credit Card Fraud Detection

IEEE Access, 2023
Imbalanced learning jeopardizes the accuracy of traditional classification models, particularly for what concerns the minority class, which is often the class of interest.
Daniele Lunghi, Gian Marco Paldino, Olivier Caelen, Gianluca Bontempi   +3 more
doaj   +1 more source

Replication Data for: Demonstration of negative refraction induced by synthetic gauge fields

, 2021
Experimental data and matlab codes for the paper "Demonstration of negative refraction induced by synthetic gauge fields
Guan, Yijun, Yang, Yihao, Ge, Yong, Jia, Ding, Chong, Yidong, Li, Rujiang, Zhang, Baile, Yuan, Shouqi, Sun, Hong Xiang, Lin, Xiao   +9 more
core   +1 more source

Related data for: Quantifying uncertainties in tropical cyclone wind hazard assessment due to synthetic track stochastic variability for Southeast Asia

, 2023
This data set contains the rate-adjusted STORM event sets and 100-year return period gust wind hazard maps related to the paper: Jian, W., Lo, E.Y-M., Stojanovski, P., & Pan, T-C. (2023).
Lo, Edmond Yat-Man, Stojanovski, Pane, Jian, Wei, Pan, Tso-Chien   +3 more
core   +1 more source

In Defense of Synthetic Data

CoRR, 2019
Discussion paper at FATES on the Web ...
Luke Rodriguez, Bill Howe
openaire   +3 more sources