Similarity between the allegiance matrices of the multiplex SC-FC graph, the FC graph alone, and the SC graph alone, as a function of the topological scale for the group. by Arian Ashourvan (6685232)

Local topological scales of hierarchical community organization in structural and functional brain graphs. by Arian Ashourvan (6685232)

DataSheet1_The evolution of flexibility and function in the Fc domains of IgM, IgY, and IgE.pdf by Rosaleen A. Calvert (10039787)

“…Introduction<p>Antibody Fc regions harbour the binding sites for receptors that mediate effector functions following antigen engagement by the Fab regions. …”

Image_2_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

Image_1_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

Image_3_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…This profile underwent differential expression analysis, WGCNA, functional enrichment, and subsequent analysis of RPL gene expression using LASSO regression, SVM-RFE, and RandomForest algorithms for hub gene screening. …”

Image_1_Multimodal Evaluation of Neurovascular Functionality in Early Parkinson's Disease.TIFF by Maria Marcella Laganà (9302738)

“…In this framework, FC and CBF might be proposed as early functional biomarkers providing meaningful insights in evaluating both disease progression and therapeutic/rehabilitation treatment outcome.…”

Table_1_Multimodal Evaluation of Neurovascular Functionality in Early Parkinson's Disease.DOCX by Maria Marcella Laganà (9302738)

“…In this framework, FC and CBF might be proposed as early functional biomarkers providing meaningful insights in evaluating both disease progression and therapeutic/rehabilitation treatment outcome.…”

Characteristics of biological processes involved in DKD. by Hailin Li (453832)

Data_Sheet_1_Consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI.docx by Minhua Yu (13211703)

“…The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. …”

Table_2_Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation.docx by Tingting Zhu (334564)

“…Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.</p>Results<p>Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. …”

Table_1_Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation.docx by Tingting Zhu (334564)

“…Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.</p>Results<p>Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. …”

Comparison of protein coding genes differentially expressed in Stage 1 and Stage 2 blood (padj < 0.05). by Peter Nambala (7245215)

Data_Sheet_1_Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume.docx by Wenjing Zhu (487218)

“…This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. …”

Ikaros and STAT5 DNA binding correlates with Ikaros- and IL-7-dependent gene expression. by Beate Heizmann (9635460)

Table_1_Dynamic Language Network in Early and Late Cantonese–Mandarin Bilinguals.DOCX by Xiaojin Liu (5398361)

“…In this study, we acquired resting-state fMRI data from early and late Cantonese (L1)–Mandarin (L2) bilinguals with high PLs of verbal fluency in both languages. We then analyzed dynamic functional connectivity (dFC) by using the sliding-windows approach, estimated the dFC states by using the k-means clustering algorithm, and calculated the dynamic topological properties of the language network for the early and late bilinguals. …”

Image 4_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg by Minhao Huang (4952764)

“…Through literature mining and GeneCards database screening, 30 programmed cell death (PCD)-related gene sets (total 11,681 genes) were curated, identifying 428 differentially expressed genes (DEGs; |log₂FC|>1, p < 0.05). A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …”

Table 2_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.xlsx by Minhao Huang (4952764)

“…Through literature mining and GeneCards database screening, 30 programmed cell death (PCD)-related gene sets (total 11,681 genes) were curated, identifying 428 differentially expressed genes (DEGs; |log₂FC|>1, p < 0.05). A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …”

Table 1_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.xlsx by Minhao Huang (4952764)

“…Through literature mining and GeneCards database screening, 30 programmed cell death (PCD)-related gene sets (total 11,681 genes) were curated, identifying 428 differentially expressed genes (DEGs; |log₂FC|>1, p < 0.05). A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …”

Image 3_Integrated machine learning analysis of 30 cell death patterns identifies a novel prognostic signature in glioma.jpeg by Minhao Huang (4952764)

“…Through literature mining and GeneCards database screening, 30 programmed cell death (PCD)-related gene sets (total 11,681 genes) were curated, identifying 428 differentially expressed genes (DEGs; |log₂FC|>1, p < 0.05). A pan-death prognostic signature (Cell-Death Score, CDS) was constructed using 114 machine learning algorithm combinations, refined via CoxBoost to select 25 key genes. …”