Deep scSTAR: Leveraging Deep Learning for the Extraction and Enhancement of Phenotype-Associated Features from Single-Cell RNA Sequencing and Spatial Transcriptomics Data

Information Science, Artificial Intelligence, Medicine, Life Sciences, Cell Biology, Immunology,
Single-cell RNA sequencing   Spatial transcriptomics   Deep learning   Phenotype-associated features   Tumor microenvironment  

In recent years, cutting-edge technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have greatly advanced the development of life sciences and clinical medicine. These technologies have revealed cellular heterogeneity and brought novel insights into major fields such as disease, development, and immunity. Howe...

Ensemble Learning Based on Matrix Completion Improves Microbe-Disease Association Prediction

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Microbiology,
microbe-disease association   ensemble learning   matrix completion   prediction algorithm   bioinformatics  

Academic Background and Research Problem Microorganisms, as one of the most widely distributed forms of life on Earth, are closely related to oceans, soil, and the human body. The human body contains approximately 350 trillion microbial cells, which are intricately linked to human health and the onset and progression of diseases. In recent years, w...

Benchmarking Copy Number Aberrations Inference Tools Using Single-Cell Multi-Omics Datasets

Information Science, Artificial Intelligence, Medicine, Oncology, Life Sciences, Cell Biology, Bioengineering, Genetics,
Single-cell RNA sequencing   Copy number aberrations   Tumor heterogeneity   Benchmarking   Multi-omics  

1. Research Background and Significance In the fields of oncology and genomics, chromosomal copy number alterations (CNAs) are a key type of genetic variation driving the occurrence and progression of cancer. CNAs not only determine tumor heterogeneity but also play a crucial role in early tumor detection, subclone evolution analysis, research on d...

Unveiling a Novel Cancer Hallmark by Evaluation of Neural Infiltration in Cancer

Medicine, Oncology, Life Sciences, Cell Biology, Immunology, Genetics,
neural infiltration   cancer hallmark   tumor microenvironment   single-cell RNA sequencing   immunotherapy  

Cancer, as a major global public health challenge, is characterized by complex mechanisms underlying its onset and progression. For a long time, processes within the tumor microenvironment (TME)—such as immunity, inflammation, and angiogenesis—have been extensively studied and considered key determinants of tumor biological behavior. In recent year...

Optimized Phenotyping of Complex Morphological Traits: Enhancing Discovery of Common and Rare Genetic Variants

Medicine, Medical Imaging, Life Sciences, Bioengineering, Genetics,
Genotype–phenotype association   Complex trait   Heritability   Facial phenotyping   3D shape  

1. Academic Background and Research Motivation In recent years, genotype–phenotype (G-P) association analysis has become a core means of revealing the genetic basis of complex traits, especially with rapid development in the study of multidimensional structural traits such as the human face, limbs, and skeleton. Traditionally, G-P analyses rely on ...

Cancer Gene Identification through Integrating Causal Prompting Large Language Model with Omics Data–Driven Causal Inference

Information Science, Artificial Intelligence, Medicine, Oncology, Life Sciences, Biochemistry, Genetics,
cancer genes   causality   large language model   multi-omics   causal learning  

Cancer gene identification is a core challenge in the fields of basic cancer research and precision medicine. Recently, a research team from Jilin University and Zhejiang Sci-Tech University published an original study titled “Cancer gene identification through integrating causal prompting large language model with omics data–driven causal inferenc...

Cox-SAGE: Enhancing Cox Proportional Hazards Model with Interpretable Graph Neural Networks for Cancer Prognosis

Information Science, Computer Science, Artificial Intelligence, Medicine, Hepatobiliary System, Oncology,
Cox proportional hazards model   cancer prognosis   graph neural networks   biomarker discovery   patient similarity graph  

1. Research Background and Disciplinary Frontiers Cancer prognosis analysis has always been a core research direction in the medical field. In recent years, with the widespread application of high-throughput sequencing technologies, scientists have been able to delve deeper into exploring molecular biomarkers and clinical characteristics of cancer ...

Consensus Statement on the Credibility Assessment of Machine Learning Predictors

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Bioengineering,
machine learning credibility   in silico medicine   causal knowledge assessment   regulatory science   error quantification   bias robustness  

1. Background: Machine Learning in Medicine and the Challenge of Credibility In recent years, the rapid development of Artificial Intelligence (AI) and Machine Learning (ML) technologies has brought about a tremendous transformation in the field of healthcare. Particularly in in silico medicine, machine learning predictors have become vital tools f...

Antigen Spatial-Matching Polyaptamer Nanostructure to Block Coronavirus Infection and Alleviate Inflammation

Chemistry, Nanoscience, Medicine, Infectious Diseases, Life Sciences, Bioengineering, Immunology, Microbiology,
antigen spatial matching   polyaptamer   coronavirus   inflammation   nanostructure   antiviral   anti-inflammatory  

Academic Background In recent years, multiple outbreaks caused by coronaviruses have occurred globally, such as SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndrome), and COVID-19 (Novel Coronavirus Pneumonia). These pandemics have not only posed a serious threat to human health but also exposed the inadequacy of emergen...

Cluster-Based Redox-Responsive Super-Atomic MRI Contrast Agents

Chemistry, Physical Chemistry, Medicinal Chemistry, Medicine, Medical Imaging, Life Sciences, Bioengineering,
redox-responsive   super-atomic clusters   MRI contrast agents   tumor microenvironment   molecular imaging  

Academic Background Magnetic Resonance Imaging (MRI) is a crucial tool in modern medical diagnostics, and its effectiveness relies heavily on the use of contrast agents (CAs). Traditional MRI contrast agents are mainly based on gadolinium (Gd) complexes. Although these agents are widely used in clinical practice, their long-term safety is controver...