Image_7_Prognostic Value of Genes and Immune Infiltration in Prostate Tumor Microenvironment.jpg by Wenguo Sun (9302267)

“…</p>Conclusion<p>CXCR4 and GPR183 participate in immune cell infiltration and function in PCa patients. The immune score, as well as the expression of CXCR4 and GPR183 in prostate cancer tissues, could be potential indexes for the prognosis of prostate cancer.…”

Image_3_Prognostic Value of Genes and Immune Infiltration in Prostate Tumor Microenvironment.jpg by Wenguo Sun (9302267)

“…</p>Conclusion<p>CXCR4 and GPR183 participate in immune cell infiltration and function in PCa patients. The immune score, as well as the expression of CXCR4 and GPR183 in prostate cancer tissues, could be potential indexes for the prognosis of prostate cancer.…”

Image_5_Prognostic Value of Genes and Immune Infiltration in Prostate Tumor Microenvironment.jpg by Wenguo Sun (9302267)

“…</p>Conclusion<p>CXCR4 and GPR183 participate in immune cell infiltration and function in PCa patients. The immune score, as well as the expression of CXCR4 and GPR183 in prostate cancer tissues, could be potential indexes for the prognosis of prostate cancer.…”

Image_1_Prognostic Value of Genes and Immune Infiltration in Prostate Tumor Microenvironment.jpg by Wenguo Sun (9302267)

“…</p>Conclusion<p>CXCR4 and GPR183 participate in immune cell infiltration and function in PCa patients. The immune score, as well as the expression of CXCR4 and GPR183 in prostate cancer tissues, could be potential indexes for the prognosis of prostate cancer.…”

Datasheet1_A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images.zip by Stefania Marcotti (5896853)

“…Here we present AFT − Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. …”

Non-random low-dimensional structure in PN-KC connectivity that is conserved across animals. by Hamza Giaffar (19590826)

“…Variance explained per dimension as a function of the PCA dimension (inset–total cumulative variance explained). …”

Image_1_Immunogenomic Profiling and Classification of Prostate Cancer Based on HIF-1 Signaling Pathway.TIF by Jukun Song (8080607)

“…The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen potential chemotherapeutic targets for the treatment of PCa. …”

Image_2_Immunogenomic Profiling and Classification of Prostate Cancer Based on HIF-1 Signaling Pathway.TIF by Jukun Song (8080607)

“…The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen potential chemotherapeutic targets for the treatment of PCa. …”

Table_1_Immunogenomic Profiling and Classification of Prostate Cancer Based on HIF-1 Signaling Pathway.docx by Jukun Song (8080607)

“…The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen potential chemotherapeutic targets for the treatment of PCa. …”

Data_Sheet_1_Neurons as Canonical Correlation Analyzers.pdf by Cengiz Pehlevan (526705)

“…First, adopting a normative approach and starting from a single-channel CCA objective function, we derive an online gradient-based optimization algorithm whose steps can be interpreted as the operation of a pyramidal neuron. …”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”

PREDICTION OF DEM PARAMETERS OF COATED FERTILIZER PARTICLES BASED ON GA-BP NEURAL NETWORK by Xin Du (208780)

“…The predicted values matched the expected output values, indicating that the GA-BP neural network can accurately predict the nonlinear function output, and the network predicted output can be approximated as the actual output of the function. …”

Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry' by Radu Stancu (21165068)

“…Distance Sensing</p><p dir="ltr">Code and data to demonstrate extracting distance sensing data from A-scans and to generate Fig. 8 using the algorithm described in Fig. 7. Functions to generate distance measurements are in 'distance_sensing_utilities.py' and an example of how to use this on data in the 'data' folder is in 'distance_sensing_example.py', which generates Fig 8. …”

DataSheet1_Identification of necroptosis-related features in diabetic nephropathy and analysis of their immune microenvironent and inflammatory response.ZIP by Kaibo Hu (13848373)

“…The principal component analysis (PCA) algorithm was utilized to calculate the necroptosis score. …”

DataSheet_1_A novel ferroptosis-related gene prognostic index for prognosis and response to immunotherapy in patients with prostate cancer.pdf by Yuliang Wang (437561)

“…Ferroptosis-related hub genes associated with DFS of PCa patients were identified by an in-depth bioinformatics analysis using a novel and comprehensive algorithm based on functional enrichment, consensus clustering, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network construction. …”

Table_1_A novel ferroptosis-related gene prognostic index for prognosis and response to immunotherapy in patients with prostate cancer.xlsx by Yuliang Wang (437561)

“…Ferroptosis-related hub genes associated with DFS of PCa patients were identified by an in-depth bioinformatics analysis using a novel and comprehensive algorithm based on functional enrichment, consensus clustering, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network construction. …”

<b>A Single-cell Transcriptomic Sequencing Dataset of Early Female and Male Chicken (</b><b><i>Gallus gallus</i></b><b>) Embryos</b> by Zhi Cao (20682218)

“…To correct for potential batch effects, the Harmony algorithm was applied. For clustering, the FindClusters function was used with a resolution of 0.4, followed by dimensionality reduction and visualization using uniform manifold approximation and projection (UMAP) and t-distributed stochastic neighbor embedding. …”

Presentation1_A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction.pdf by Pengxiang Zheng (7125176)

“…<p>Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. …”

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making by Xiaofei Zhang (16483224)

“…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …”

Table_4_Comprehensive Analysis of m5C Methylation Regulatory Genes and Tumor Microenvironment in Prostate Cancer.docx by Guopeng Yu (730431)

“…These findings may improve our understanding of m5C regulatory genes in the tumor biology of PCa.</p>…”