Current applications of machine learning for spinal cord tumors
Spinal cord tumors constitute a diverse group of rare neoplasms associated with significant
mortality and morbidity that pose unique clinical and surgical challenges. Diagnostic …
mortality and morbidity that pose unique clinical and surgical challenges. Diagnostic …
State-of-the-Art and New Treatment Approaches for Spinal Cord Tumors
C Kumawat, T Takahashi, I Date, Y Tomita, M Tanaka… - Cancers, 2024 - mdpi.com
Simple Summary Spinal cord tumors encompass a diverse range of rare neoplasms
originating from tissues in and around the spinal canal. Traditional treatment modalities like …
originating from tissues in and around the spinal canal. Traditional treatment modalities like …
Computational model for disease research
Computational analysis of vast public and private omics data [1–5] generated by high-
throughput technologies [6, 7] aids in deciphering complex mechanisms [8–11] and relevant …
throughput technologies [6, 7] aids in deciphering complex mechanisms [8–11] and relevant …
Pan‐Cancer Single‐Cell and Spatial‐Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy
C Liu, J Xie, B Lin, W Tian, Y Wu, S Xin… - Advanced …, 2024 - Wiley Online Library
The heterogeneity of macrophages influences the response to immune checkpoint inhibitor
(ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI …
(ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI …
MutBLESS: A tool to identify disease-prone sites in cancer using deep learning
M Pandey, MM Gromiha - Biochimica et Biophysica Acta (BBA)-Molecular …, 2023 - Elsevier
Understanding the molecular basis and impact of mutations at different stages of cancer are
long-standing challenges in cancer biology. Identification of driver mutations from …
long-standing challenges in cancer biology. Identification of driver mutations from …
InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data
Cancer driver genes are critical in driving tumor cell growth, and precisely identifying these
genes is crucial in advancing our understanding of cancer pathogenesis and developing …
genes is crucial in advancing our understanding of cancer pathogenesis and developing …
CarbDisMut: database on neutral and disease-causing mutations in human carbohydrate-binding proteins
Protein-carbohydrate interactions are involved in several cellular and biological functions.
Integrating structure and function of carbohydrate-binding proteins with disease-causing …
Integrating structure and function of carbohydrate-binding proteins with disease-causing …
Discovering pathway biomarkers of hepatocellular carcinoma occurrence and development by dynamic network entropy analysis
C Shen, Y Cao, G Qi, J Huang, ZP Liu - Gene, 2023 - Elsevier
Objective Gene expression profiling techniques measure the transcription of thousands of
genes in a parallel manner. With more and more hepatocellular carcinoma (HCC) …
genes in a parallel manner. With more and more hepatocellular carcinoma (HCC) …
Loss of PTPRS elicits potent metastatic capability and resistance to temozolomide in glioblastoma
Y Zhang, L Chang, P Huang, M Cao… - Molecular …, 2024 - Wiley Online Library
Glioblastoma (GBM) is the most aggressive brain tumor type with worse clinical outcome
due to the hallmarks of strong invasiveness, high rate of recurrence, and therapeutic …
due to the hallmarks of strong invasiveness, high rate of recurrence, and therapeutic …
From Code to Cure: The Impact of Artificial Intelligence in Biomedical Applications
MM Gromiha, P Preethi, M Pandey - BioMedInformatics, 2024 - mdpi.com
Artificial intelligence (AI), a branch of computer science, involves developing intelligent
computer programs to mimic human intelligence and automate various processes. AI has …
computer programs to mimic human intelligence and automate various processes. AI has …