Table 3_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.docx by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”

Load frequency control performance enhancement of an electric vehicle integrated time-delay multi-microgrid system by Bhuvnesh Khokhar (19665602)

“…A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the M<i>μ</i>G system. …”

The immune microenvironment association of CENPA in cancers. by Hengrui Liu (2059750)

Supplementary file 1_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.d... by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”

A. Mean change from baseline on Cognitive Ability Scores. by Carol Kotliar (22351525)

Cell2Spatial enables versatile applications across various analytical domains. by Huamei Li (8815955)

pone.0331193.t003 - by Carol Kotliar (22351525)

“…The MTT24.5 program aims to stimulate brain function through a combination of new knowledge acquisition (DATA) and learning techniques (TECHS), organized into a systematic algorithm. …”

Baseline characteristics by group. by Carol Kotliar (22351525)

“…The MTT24.5 program aims to stimulate brain function through a combination of new knowledge acquisition (DATA) and learning techniques (TECHS), organized into a systematic algorithm. …”

Data Sheet 3_Continuous wavelet based transfer function analysis of cerebral autoregulation dynamics for neuromonitoring using near-infrared spectroscopy.pdf by Marcus Thudium (6441863)

“…Derived parameters like cerebral oxygenation index or Fast Fourier Transform based coherence estimates between blood pressure and cerebral blood flow have their limitations of use for stationary data and low time resolution. Wavelet transfer function analysis can be employed to estimate coherence, gain and phase relationship between two signals without these restrictions.…”

Data Sheet 1_Continuous wavelet based transfer function analysis of cerebral autoregulation dynamics for neuromonitoring using near-infrared spectroscopy.pdf by Marcus Thudium (6441863)

“…Derived parameters like cerebral oxygenation index or Fast Fourier Transform based coherence estimates between blood pressure and cerebral blood flow have their limitations of use for stationary data and low time resolution. Wavelet transfer function analysis can be employed to estimate coherence, gain and phase relationship between two signals without these restrictions.…”

Data Sheet 2_Continuous wavelet based transfer function analysis of cerebral autoregulation dynamics for neuromonitoring using near-infrared spectroscopy.pdf by Marcus Thudium (6441863)

“…Derived parameters like cerebral oxygenation index or Fast Fourier Transform based coherence estimates between blood pressure and cerebral blood flow have their limitations of use for stationary data and low time resolution. Wavelet transfer function analysis can be employed to estimate coherence, gain and phase relationship between two signals without these restrictions.…”

Data Sheet 4_Continuous wavelet based transfer function analysis of cerebral autoregulation dynamics for neuromonitoring using near-infrared spectroscopy.pdf by Marcus Thudium (6441863)

“…Derived parameters like cerebral oxygenation index or Fast Fourier Transform based coherence estimates between blood pressure and cerebral blood flow have their limitations of use for stationary data and low time resolution. Wavelet transfer function analysis can be employed to estimate coherence, gain and phase relationship between two signals without these restrictions.…”

Supplemental Tables S1 and S2 for Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks by Diana Murray (16859046)

“…The integrated method has better performance and identifies more high-confidence interactions than any of the component methods. The AF3Complex algorithm was used to predict the structures of 374 PPIs with a large fraction having at least partially overlapping interfaces with PrePPI models of the same complex. …”

Real time spike sorting with latencies in the range of synaptic transmission. by Tjitse van der Molen (20391106)

Data analyzed for the article of <b>Evaluating photoplethysmography-based pulsewave parameters and composite scores for assessment of cardiac function: A comparison with echocardio... by Kulin (20907929)

“…Concurrently, echocardiographic parameters were derived by averaging the data from 1-3 heartbeats, allowing for a direct comparison of cardiac function assessments between the two techniques, by the following. …”

Graphical representation of the diffuse interface approach in one dimension. by Martina Bukač (20161460)

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

The modified SarcGraph pipeline. by Saeed Mohammadzadeh (13492285)

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”

Visualization of the image segmentation and labeling pipeline for the first frame of an example movie. by Miriam Schnitzerlein (21446136)