Image 1_Identification and validation of key biomarkers of the glycolysis-ketone body metabolism in heart failure based on multi-omics and machine learning.pdf by Na Xiao (327834)

“…Candidate genes were refined using machine learning algorithms (LASSO regression and Boruta), with functional enrichment assessed via Gene Set Enrichment Analysis (GSEA). …”

Phase stability at interfaces (dataset) by J Pitfield (21962924)

Exploring Human Brain Metabolism via Genome-Scale Metabolic Modeling with Highlights on Multiple Sclerosis by Mustafa Sertbas (18211859)

“…Cerebral dysfunctions give rise to a wide range of neurological diseases due to the structural and functional complexity of the human brain stemming from the interactive cellular metabolism of its specific cells, including neurons and glial cells. …”

Exploring Human Brain Metabolism via Genome-Scale Metabolic Modeling with Highlights on Multiple Sclerosis by Mustafa Sertbas (18211859)

“…Cerebral dysfunctions give rise to a wide range of neurological diseases due to the structural and functional complexity of the human brain stemming from the interactive cellular metabolism of its specific cells, including neurons and glial cells. …”

An miRNA panel to predict RRiF. by Nabarun Chakraborty (535772)

The SHAP (Shapley Additive exPlanations) values of observed variables. by Xin Zhang (35492)

Clinically relevant subgroups of T2DM patients using unsupervised clustering analysis by Evans A. Adu (7524140)

Worm Tracking Module. by Xiaoke Liu (11388323)

Direction of change and range of change. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

Multi-condition global optimization process. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

Two-stage optimization process. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

Multi-condition local fine optimization process. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

FFD parametric method modeling flow chart. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

FFD technology. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

Position of the optimization variable. by Yesong Wang (331723)

“…We propose two distinct spline function parameterization techniques: a global mapping model for Bezier surfaces and a local mapping model for Free-Form Deformation (FFD) control bodies. …”

SHAP values for chromatin-associated proteins profiled in Wang et al. [22] (A) Chromatin-associated proteins and histone marks relevant for this model. by Kashyap Chhatbar (9515350)

SHAP values for H3K4me3, co-occupying PRC1 (RING1B) and PRC2 (SUZ12) components and their catalytic marks across multiple time points following RING1B degradation. by Kashyap Chhatbar (9515350)

SHAP values for co-occupying PRC1 (RING1B) and PRC2 (SUZ12) components and their catalytic marks. by Kashyap Chhatbar (9515350)

SHAP values for SET1A, H3K4me3 and ZC3H4. by Kashyap Chhatbar (9515350)

Data Sheet 1_Development and validation of a predictive model for postoperative functional recovery in patients with spontaneous intracerebral hemorrhage.pdf by Ziming Jiang (9741389)

“…A prognostic nomogram integrating imaging characteristics and clinical parameters was developed to predict 90-day functional recovery (modified Rankin Scale ≤2). Feature selection employed the Boruta algorithm, followed by multivariable logistic regression. …”