Genetics

Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.

Breast cancer (BRCA) continues to pose a serious risk to women's health worldwide. Neoadjuvant chemo...

Tumor-educated platelets in lung cancer.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), w...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical ...

Revealing the Oxidative Stress-Related Molecular Characteristics and Potential Therapeutic Targets of Schizophrenia through Integrated Gene Expression Data Analysis.

Schizophrenia is a severe mental disorder characterized by oxidative stress imbalances. The underlyi...

Role of electrostatics in cold adaptation: A comparative study of eury- and stenopsychrophilic triose phosphate isomerase.

Psychrophilic (cold-active) organisms have developed enzymes that facilitate sufficient metabolic ac...

Peripheral blood immune landscape and NXPE3 as a novel biomarker for hypertensive intracerebral hemorrhage risk prediction and targeted therapy.

We employed bulk RNA-seq and scRNA-seq techniques to analyze the immune dysregulation in patients wi...

Multifaceted profiling of virus-specific CD8 T cells reveals distinct immune signatures against cytomegalovirus infection states during pregnancy.

Anti-cytomegalovirus (CMV) serological testing, including the IgG avidity index (AI), is used to ass...

Identification of M1 macrophage infiltration-related genes for immunotherapy in Her2-positive breast cancer based on bioinformatics analysis and machine learning.

Over the past several decades, there has been a significant increase in the number of breast cancer ...

Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions.

Using millions of methylation segments, we developed DiffuCpG, a generative artificial intelligence ...

Comparative analysis of AI models in disseminating genetic counseling knowledge for gynecologic cancers.

Targeting the MAPK signaling pathway: implications and prospects of flavonoids in 3P medicine as modulators of cancer cell plasticity and therapeutic resistance in breast cancer patients.

Cancer drug resistance poses a significant challenge in oncology, primarily driven by cancer cell pl...

The AI revolution comes to protein sequencing.

By identifying unknown proteins, new systems could aid research in many areas.

Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning.

This study evaluates the concordance between RNA sequencing (RNA-Seq) and NanoString technologies fo...

Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics.

Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitativ...

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.

BACKGROUND: The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in K...

Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.

Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to i...

Exploring 4 generation EGFR inhibitors: A review of clinical outcomes and structural binding insights.

Epidermal growth factor receptor (EGFR) is a potential target for anticancer therapies and plays a c...

Ivermectin performance against equine strongylids: Efficacy, egg reappearance periods, and fecal egg counting method comparison.

Equine strongylids are ubiquitous and can cause severe health issues. Anthelmintic resistance is wid...

Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.

BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely compl...

DTreePred: an online viewer based on machine learning for pathogenicity prediction of genomic variants.

BACKGROUND: A significant challenge in precision medicine is confidently identifying mutations detec...

Utilizing a deep learning model based on BERT for identifying enhancers and their strength.

An enhancer is a specific DNA sequence typically located within a gene at upstream or downstream pos...