Digitally Assisted Single-Particle Tracking for Accurate Analysis of Complicated Cargo Transport Dynamics in Microtubule Networks by Xiaodong Cheng (8947)

“…Intracellular transport is a fundamental process crucial for cellular function, driven by the coordinated action of motor proteins that move cargo along microtubule tracks. …”

Digitally Assisted Single-Particle Tracking for Accurate Analysis of Complicated Cargo Transport Dynamics in Microtubule Networks by Xiaodong Cheng (8947)

“…Intracellular transport is a fundamental process crucial for cellular function, driven by the coordinated action of motor proteins that move cargo along microtubule tracks. …”

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). …”

Image 1_Integrating bioinformatics and machine learning analyses to identify immune-related secretory proteins and therapeutic small-molecule drugs in calcific aortic valve disease... by Xiang Zhang (19800)

“…Protein-protein interaction (PPI) networks, functional enrichment analysis, and Connectivity Map (cMAP) prediction were conducted to identify potential therapeutic targets. …”

Table 1_Integrating bioinformatics and machine learning analyses to identify immune-related secretory proteins and therapeutic small-molecule drugs in calcific aortic valve disease... by Xiang Zhang (19800)

“…Protein-protein interaction (PPI) networks, functional enrichment analysis, and Connectivity Map (cMAP) prediction were conducted to identify potential therapeutic targets. …”

Image 2_Integrating bioinformatics and machine learning analyses to identify immune-related secretory proteins and therapeutic small-molecule drugs in calcific aortic valve disease... by Xiang Zhang (19800)

“…Protein-protein interaction (PPI) networks, functional enrichment analysis, and Connectivity Map (cMAP) prediction were conducted to identify potential therapeutic targets. …”

Supplementary file 1_SLC11A1 protein as a key regulator of iron metabolism, ferroptosis mediator, and putative therapeutic target in nonalcoholic fatty liver disease: an integrated... by Yang Wang (5921)

“…</p>Methods<p>This study utilized NAFLD datasets from the GEO database and applied bioinformatics approaches to identify iron metabolism and ferroptosis-related differentially expressed genes (DEGs) in NAFLD. Key regulatory proteins—ERN1, SLC11A1, MYC, TLR7, and PPARGC1A—were screened using weighted gene co-expression network analysis (WGCNA) and a machine learning algorithm (LASSO). …”

DataSheet5_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.DOCX by Bao Li (1333650)

DataSheet8_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet3_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet7_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet6_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet4_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet2_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

DataSheet1_Identification of immune microenvironment subtypes and clinical risk biomarkers for osteoarthritis based on a machine learning model.CSV by Bao Li (1333650)

Data Sheet 1_Inflammatory imbalance and activation deficits in T cells of myasthenia gravis patients revealed by proteomic profiling.pdf by Amol K. Bhandage (6083420)

“…In contrast, activated CD4+ and CD8+ cells from MG patients exhibited a blunted secretion profile compared to HC, suggesting functional exhaustion. Furthermore, MG-ADL scores correlated with the secretion levels of 14 proteins from resting CD4+ cells, including seven cytokines, five chemokines, and two matrix metalloproteins. …”

Expanded Structural and Computational Evaluation of Mitofusin-2 Variants of Unknown Significance by Kimiya Shafaat (22416388)

Image5_Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.jpeg by Yingquan Ye (13036128)

“…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”

DataSheet1_Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.ZIP by Yingquan Ye (13036128)

“…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”

Image2_Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.jpeg by Yingquan Ye (13036128)

“…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”