Image 5_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 3_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.jpeg حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 4_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 2_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Longitudinal trajectories of functional network development across the birth transition. حسب Lanxin Ji (20290942)

"…Stronger RSFC within networks affirms validity of the network clustering algorithm. (B) Functional parcels and networks. (C) Age effect on the ROI-to-ROI functional connectivity. …"

Screening potential diagnostic biomarkers for PLA2R‑associated idiopathic membranous nephropathy by WGCNA analysis and LASSO algorithm حسب Jinxu Huang (7865069)

Elastin-Based Janus Hydrogel Tape with Adhesive, Stretchable, and Conductive Properties for Soft Bioelectronic Applications حسب Zhongwei Guo (240554)

"…Benefiting from the NHS ester group, the bottom layer can rapidly and robustly adhere to biological tissues. …"

Effect of Mitophagy Score on Immunotherapy for Different Datasets. حسب Jie Chu (293795)

Executable Power: Syntax as Infrastructure in Predictive Societies حسب Agustin V. Startari (21179732)

Developing an Integrated Framework to Guide the Ecological Design of Electrical and Electronic Equipment حسب Guo-Guo Liu (21625651)

"…This study developed a framework that integrates knowledge graphs, quality function deployment, and a Pareto-optimal algorithm to guide the ecological design of EEE, achieving market demand evaluation, technical feasibility analysis, and optimal design scheme generation. …"

Overall method pipeline. حسب Thomas Durantel (20933812)

Functional and Structural Characterization of Mechanosensitive Piezo1 Channel in Disease حسب Sophia Liu (722004)

"…AF3 predictions closely matched known protein structures (r.m.s.d. < 0.5), and in-silico mutagenesis revealed that several variants caused cavity alterations, hydrogen bond or salt bridge disruptions, and buried-to-exposed transitions. However, most algorithms struggled to distinguish gain-of-function (GoF) from loss-of-function (LoF) variants, with GoF variants showing lower pathogenicity scores despite clinical relevance.…"

The structural mutation of neuroevolution. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

The genome coding scheme. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

The speciation of ANEAT model evolution. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

The analysis of feature importance. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

S1 Data - حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

The fitness of ANEAT model evolution. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"

The structure of the data sample. حسب Wenbing Shi (5806160)

"…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …"