AIMC Topic: Transcriptome

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Computer vision for image-based transcriptomics.

Methods (San Diego, Calif.)
Single-cell transcriptomics has recently emerged as one of the most promising tools for understanding the diversity of the transcriptome among single cells. Image-based transcriptomics is unique compared to other methods as it does not require conver...

De novo transcriptome assembly of pummelo and molecular marker development.

PloS one
Pummelo (Citrus grandis) is an important fruit crop worldwide because of its nutritional value. To accelerate the pummelo breeding program, it is essential to obtain extensive genetic information and develop relative molecular markers. Here, we obtai...

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

Computational biology and chemistry
Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene...

Dissecting cross-lineage tumourigenesis under p53 inactivation through single-cell multi-omics and spatial transcriptomics.

Clinical and translational medicine
BACKGROUND: Tumour suppressor genes, exemplified by TP53 (encoding the human p53), function as critical guardians against tumourigenesis. Germline TP53-inactivating mutations underlie Li-Fraumeni syndrome, a hereditary cancer predisposition disorder ...

GPSai: A Clinically Validated AI Tool for Tissue of Origin Prediction during Routine Tumor Profiling.

Cancer research communications
UNLABELLED: A subset of cancers present with unclear or potentially incorrect primary histopathologic diagnoses, including cancers of unknown primary (CUP). We aimed to develop and validate an artificial intelligence (AI) tool, Genomic Probability Sc...

Genetic and molecular underpinnings of the link between rheumatoid arthritis and myasthenia gravis: Insights from GWAS and transcriptomic analyses.

Clinical rheumatology
BACKGROUND: Although studies have shown that patients with rheumatoid arthritis (RA) are at a higher risk of developing myasthenia gravis (MG), the causal relationship and shared genetic basis between these two diseases have not been fully investigat...

Developing a Panel of Shared Susceptibility Genes as Diagnostic Biomarkers for chronic obstructive pulmonary disease and Heart Failure.

Computers in biology and medicine
AIM: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) are closely intertwined comorbidities that present significant clinical challenges due to the poorly understood pathophysiological mechanisms driving their coexistence. In this ...

Genetic features for drug responses in cancer - Investigating an ensemble-feature-selection approach.

Computers in biology and medicine
Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an ensemble of machine learning algorithms to analyze the correlation between genetic and transcriptomic...

Signature gene expression model for quantitative evaluation of MASH-like liver injury in mice.

Toxicology and applied pharmacology
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of chronic pathologic conditions strongly associated with metabolic syndrome and affects approximately 38 % of the global population. Untreated MASLD may progress to metab...

Role of machine learning in molecular pathology for breast cancer: A review on gene expression profiling and RNA sequencing application.

Critical reviews in oncology/hematology
INTRODUCTION: Breast cancer is the most prevalent cancer among women, with growing incidence and mortality rates. Regardless of remarkable progress in cancer research, breast cancer remains a major concern due to its complex nature. These factors und...