Genetics

The absence of both RIBC1 and RIBC2 induces decreased sperm motility and litter size in male mice.

BACKGROUND: RIBC1 (RIB43A domain with coiled-coils 1) and RIBC2 (RIB43A domain with coiled-coils 2) are homolog proteins of RIB43a which is localized to microtubules in the cilia and flagella of unicellular organisms. Cryo-electron microscopy and artificial intelligence studies showed that RIBC1 and RIBC2 are microtubule inner proteins (MIPs) localized in the inner lumen of the doublet microtubule...

Development and validation of an interpretable machine learning model for diagnosing pathologic complete response in breast cancer.

BACKGROUND: Pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT) is a critical prognostic marker for patients with breast cancer, potentially allowing surgery omission. However, noninvasive and accurate pCR diagnosis remains a significant challenge due to the limitations of current imaging techniques, particularly in cases where tumors completely disappear post-NACT.

Harnessing genotype and phenotype data for population-scale variant classification using large language models and bayesian inference.

Variants of Uncertain Significance (VUS) in genetic testing for hereditary diseases burden patients and clinicians, yet clinical data that could reduc...

Improved Pine Wood Nematode Disease Diagnosis System Based on Deep Learning.

Pine wilt disease caused by the pine wood nematode, , has profound implications for global forestry ecology. Conventional PCR methods need long operat...

Clinical performance of a machine learning-based model for detecting lymph node metastasis in papillary thyroid carcinoma: A multicenter study.

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with a generally favorable prognosis, but lymph node metastasis (LNM) complicates t...

The inconsistent pathogenesis of endometriosis and adenomyosis: insights from endometrial metabolome and microbiome.

UNLABELLED: Endometriosis (EM) and adenomyosis (AM) are interrelated gynecological disorders characterized by the aberrant presence of endometrial tis...

Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.

OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics features in bladder cancer (BLCA) using single-ce...

The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and...

Transfer learning of multicellular organization via single-cell and spatial transcriptomics.

Biological tissues exhibit complex gene expression and multicellular patterns that are valuable to dissect. Single-cell RNA sequencing (scRNA-seq) pro...

Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions....

Predicting single-cell protein production from food-processing wastewater in sequencing batch reactors using ensemble learning.

Producing single-cell protein (SCP) from food-processing wastewater offers a sustainable approach to resource recovery, animal feed production, and wa...

Intersecting impact of CAG repeat and huntingtin knockout in stem cell-derived cortical neurons.

Huntington's Disease (HD) is caused by a CAG repeat expansion in the gene encoding huntingtin (HTT). While normal HTT function appears impacted by the...

Construction of a deep learning model and identification of the pivotal characteristics of FGF7- and MGST1- positive fibroblasts in heart failure post-myocardial infarction.

Dysregulation of fibroblast function is closely associated with the occurrence of heart failure after myocardial infarction (post-MI HF). Myocardial f...

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental factors, with unclear pathogenesis. This study aims t...

Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning.

As a newly discovered histone modification, abnormal lactation has been found to be present in and contribute to the development of various cancers. T...

EBMGP: a deep learning model for genomic prediction based on Elastic Net feature selection and bidirectional encoder representations from transformer's embedding and multi-head attention pooling.

Enhancing early selection through genomic estimated breeding values is pivotal for reducing generation intervals and accelerating breeding programs. R...

Intelligent Care: A Scientometric Analysis of Artificial Intelligence in Precision Medicine.

The integration of advanced computational methods into precision medicine represents a transformative advancement in healthcare, enabling highly perso...

Deep learning model based on ultrasound images predicts BRAF V600E mutation in papillary thyroid carcinoma.

BRAF V600E mutation status detection facilitates prognosis prediction in papillary thyroid carcinoma (PTC). We developed a deep-learning model to dete...

Consecutive low-frequency shifts in A/T content denote nucleosome positions across microeukaryotes.

Nucleosomes are the basic repeating unit, each spanning ≈150bp, that structures DNA in the nucleus and their positions have major consequences on gene...

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

BACKGROUND: A gene regulatory network (GRN) is a graph-level representation that describes the regulatory relationships between transcription factors ...