Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

Data Sheet 1_Identification of novel lipid metabolism-related biomarkers of aortic dissection by integrating single-cell RNA sequencing analysis and machine learning algorithms.zip by Zhechen Li (15456929)

“…Functional characterization included cell-cell communication analysis and pseudo-time trajectory reconstruction to elucidate the roles of candidate genes in aortic dissection pathogenesis.…”

A synopsis of the research design and flowchart. by Ravinder Sharma (13154079)

“…We believe that our findings could open promising avenues for potential therapeutic interventions in ChAc.…”

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)

“…</p>Methods<p>We aimed to extend the previously described Grinsted wavelet package with rectified bias of power and transfer function gain estimation of cerebral autoregulation assessment. …”

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

“…</p>Methods<p>We aimed to extend the previously described Grinsted wavelet package with rectified bias of power and transfer function gain estimation of cerebral autoregulation assessment. …”

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

“…</p>Methods<p>We aimed to extend the previously described Grinsted wavelet package with rectified bias of power and transfer function gain estimation of cerebral autoregulation assessment. …”

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

“…</p>Methods<p>We aimed to extend the previously described Grinsted wavelet package with rectified bias of power and transfer function gain estimation of cerebral autoregulation assessment. …”

Comparison of immune cell infiltration between high-risk and low-risk sample groups. by Changquan Shang (21647625)

Calculating the TAMs-associated score. by Changquan Shang (21647625)

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…<p dir="ltr">This dataset contains the data used in the article <a href="https://academic.oup.com/aob/advance-article/doi/10.1093/aob/mcaf043/8074229" rel="noreferrer" target="_blank">"Machine Learning and digital Imaging for Spatiotemporal Monitoring of Stress Dynamics in the clonal plant Carpobrotus edulis: Uncovering a Functional Mosaic</a>", which includes the complete set of collected leaf images, image features (predictors) and response variables used to train machine learning regression algorithms.…”

Table 2_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”

Table 1_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”

Table 3_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”

Test data on the ability to escape local optima. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. The DGEP model serves to enhance GEP performance through the effective maintenance of diversity and improved global search functions. …”

Summary of the notations. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. The DGEP model serves to enhance GEP performance through the effective maintenance of diversity and improved global search functions. …”

Comparison of population diversity. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. The DGEP model serves to enhance GEP performance through the effective maintenance of diversity and improved global search functions. …”

Test data on mining capacity. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. The DGEP model serves to enhance GEP performance through the effective maintenance of diversity and improved global search functions. …”

Comparison of standard GEP and DGEP. by Kejia Liu (5699651)

“…The escape rate from local optima within DGEP reached 35% higher than what standard GEP could achieve. The DGEP model serves to enhance GEP performance through the effective maintenance of diversity and improved global search functions. …”