Genetics

Inferring gene regulatory networks via adversarially regularized directed graph autoencoder.

Revealing complete gene regulatory networks (GRNs) is important for a deeper understanding of biological processes. Although numerous GRN inference methods have been proposed, they are not only struggle to cope with the complex topology of GRNs, but also do not take into account the non-identical distribution property of gene expression data. To address the above challenges, We propose to infer GR...

Inference of drowning sites of cases in the Pearl river based on microbial community profiling and random forest algorithm.

Accurate inference of drowning sites remains a critical challenge in forensic investigations, particularly for corpses recovered from dynamic aquatic environments. Conventional methods, such as diatom testing, are limited by the absence or scarcity of diatoms in certain water bodies, labor-intensive morphological identification, and challenges in distinguishing morphologically similar species. In ...

Uncovering the Dynamics of Mucosa-Associated Microbiota in Postoperative Recurrence of Crohn's Disease.

BACKGROUND & AIMS: About 50% to 75% of patients with Crohn's disease (CD) need bowel resection. Postoperative recurrence of CD is frequent. Here, we i...

Large-scale analysis of DNA quantification metrics and SNP sequencing performance in unidentified human remains.

Massively parallel sequencing (MPS)-based single nucleotide polymorphism (SNP) profiling is being increasingly used in forensic DNA testing, yet the i...

Integrative bioinformatics and machine learning combined with experimental validation in a doxorubicin-induced model identify BACH2, NXPH4, CD1E, and LIF as sodium overload-related molecular signatures in dilated cardiomyopathy.

INTRODUCTION: Dilated cardiomyopathy (DCM) is a leading cause of heart failure and remains a major clinical challenge due to its complex etiology and ...

Transcriptome Profiling of Peripheral Blood for Inflammatory Subtype Classification and Diagnostic Model Construction in Asthma.

OBJECTIVE: This study aimed to identify inflammatory subtypes of asthma using peripheral blood transcriptomics and to derive candidate biomarkers supp...

Machine learning-based model for prediction of KCNJ5 mutation in unilateral primary aldosteronism based on [68Ga]Ga-Pentixafor PET/CT.

A machine learning framework reveals key drivers of cytokine responses in a healthy human cohort.

Population based studies are essential to evaluate the impact of the genetic and environmental determinants that influence the regulation of the human...

Three-dimensional genome reorganization foreshadows zygotic genome activation in Drosophila.

How chromatin conformation relates to chromatin state remains a central challenge in genome regulation. Here we present Pico-C, a low-input Micro-C ap...

Toxicogenomic Characterization of Perfluorooctanoic Acid-Associated Bladder Carcinogenesis.

OBJECTIVE: This study aims to bridge toxicological target prediction and bladder cancer transcriptomics by systematically identifying molecular signat...

NetG2P: Network-based genotype-to-phenotype transformation identifies key signaling crosstalk for prognosis in pan-cancer study.

BACKGROUND: Despite advances in whole-genome sequencing and identifying cancer-associated genetic alterations, understanding the influence of multiple...

RNA Dynamics and Interactions Revealed Through Atomistic Simulations.

RNA function is deeply intertwined with its conformational dynamics. In this review, we survey recent advances in the use of atomistic molecular dynam...

Screening Biomarkers for Nerve Injury Using Weighted Gene Co‐Expression Network Analysis and Machine Learning.

BACKGROUND: Nerve injury triggers complex molecular responses involving immune activation and neuronal damage, yet the key regulatory genes and their ...

Systematic evaluation of computational methods for cell segmentation.

Cell segmentation plays a crucial role in elucidating cell structure and function, understanding disease mechanisms, and aiding pathological diagnosis...

Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.

Increasing evidence suggests that Graves' disease (GD) may increase the risk of thyroid cancer (THCA), but diagnostic biomarkers associated with it re...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Breaking resistance in BRAF-mutant Melanoma: Novel strategies and biomarkers for optimizing targeted therapies.

In metastatic melanoma with a BRAFV600 mutation, inhibitors of BRAF and MEK have improved survival. Resistance may be acquired through late genetic al...

Subclassification of Small Cell Lung Cancer Based on Gene Expression Signatures and Machine Learning.

Small-cell lung cancer (SCLC) is frequently subdivided into four molecular subtypes according to the activity of key transcription factors (TFs) NEURO...

Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.

Colorectal cancer (CRC) remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progre...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS score genes has limited efficacy in differentiati...