Datasets

subject: Machine Learning

Total is 18 Results
Genome-wide, Organ-delimited gene regulatory networks (OD-GRN) provide high accuracy in candidate Transcription Factor (TF) selection across diverse processes

10.4231/50R5-EM83

Karen Hudson , Kranthi K Varala ORCID logo , Ying Li

01/04/2024

Organ-specific gene expression datasets that include hundreds to thousands of experiments allow reconstruction of gene regulatory networks and discovery of transcriptional regulators various pathways and processes.

Arabidopsis thaliana Gene regulatory networks k-nearest neighbor (kNN) linear support vector machines (SVM) Machine Learning Systems biology

General Aviation Flight Phase Identification using Automatic Dependent Surveillance-Broadcast (ADS-B)

10.4231/X0HZ-MF23

John H Mott , Qilei Zhang ORCID logo

08/23/2021

Dataset including KLAF ADS-B data and synthetic flight data for clustering validation purposes.

ADS-B Aviation Technology Clustering Machine Learning

RoboMal Malware Detection Dataset

10.4231/YN7G-H807

Byung-cheol Min ORCID logo , Haozhe Zhou , Richard Voyles , Upinder Kaur ORCID logo , Xiaxin Shen

10/15/2021

The RoboMal Dataset consists of 450 binary executables designed to facilitate malware detection in robotic software.

Engineering Technology Machine Learning malware Python Robotics security

A deep learning neural network to extract of P- and S-wave transit times from Vertical Seismic Profile (VSP)

10.4231/TT0F-KH40

Douglas R Schmitt ORCID logo , Oumeng Zhang ORCID logo

07/23/2024

This archive contains the training dataset and the Python code to train a deep learning neural net that aims to extract separately P and S wave arrival transit times from synthetic common shot gathers (CSG) in a deviated borehole geometry.

deep learning Machine Learning Machine Learning and Geophysical Signals seismic behavior

Deep Learning of CYP450 Binding of Small Molecules by Quantum Information

10.4231/SCF2-QJ02

Koushiki Basu ORCID logo , Nicholas Huls , Shan Lu , Tonglei Li ORCID logo

11/06/2024

We implemented the Manifold Embedding of Molecular Surface approach, which retains the quantum mechanical characteristics of molecules, to predict a drug's likelihood of binding to cytochrome P450 enzymes by deep learning.

deep learning Informatics Machine Learning Molecular Pharmacology

Data for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/0PG5-KC30

Pin-ching Li , Sayan Dey ORCID logo , Venkatesh Mohan Merwade ORCID logo

01/23/2023

This resource contains the data used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) covariate shift Hydrology Machine Learning prediction in ungauged basin Random Forest streamflow prediction

Codes for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/B783-2C47

Pin-ching Li , Sayan Dey ORCID logo , Venkatesh Mohan Merwade ORCID logo

01/23/2023

This resource contains codes used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)

Artificial Neural Network (ANN) Machine Learning Random Forest streamflow prediction

Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling

10.4231/FPHP-0153

Meng-yang Lin , Mitchell R Tuinstra ORCID logo

02/11/2022

High-throughput hyperspectral imaging in corn and sorghum can be used in multi-species models to predict water and nitrogen status of plants within and across these crop species.

Abiotic stress Agronomy Corn Ecophysiology High-throughput Phenotyping Machine Learning nitrogen content partial least square regression relative water content Remote Sensing Sorghum

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