A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…”

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

Related Work Summary. by Hend Bayoumi (22693738)

Optimal Drug-Target Docking Visualization. by Qijun Wo (12992781)

Homomorphic binary tree. by Jianhua He (341366)

Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. by Danish M. Anwer (15383441)

Most informative genes for predicting cell-line responses for Gefitinib. by Sofia P. Miranda (11418930)

IFS curves of two classification algorithms based on feature list yielded by MCFS. by Zhan Dong Li (12481390)

Algorithm 2: Maintain inhibitory densities coherence. by Dimitri Rodarie (10148838)

Screening MMRG gene variables associated with UC based on the optimal machine learning model. by Li Li (14993)

DataSheet1_Establishment and Optimization of Radiomics Algorithms for Prediction of KRAS Gene Mutation by Integration of NSCLC Gene Mutation Mutual Exclusion Information.DOCX by Jingyi Wang (550305)

“…<p>Purpose: To assess the significance of mutation mutual exclusion information in the optimization of radiomics algorithms for predicting gene mutation.…”

Algorithm 1: Cap inhibitory densities to number of neurons. by Dimitri Rodarie (10148838)

Table1_Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms.DOCX by Weimin Li (131040)

“…In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. …”

Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Image_1_Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization.TIF by Lin Cui (163750)

UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms. by Fatemeh Keikha (20917848)