Genetics

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi-Omics Analysis.

Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effect declines as the disease progresses. Currently, our research on osteosarcoma is not enough to meet the clinical needs. Exosomes play a critical role ...

A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.

Improved scalability of high-throughput RNA-sequencing technologies has contributed to their proposed use in regulatory contexts for chemical hazard identification. However, the high dimensionality and size of these transcriptomic data sets present a formidable obstacle for utilizing these data to address gaps in chemical safety information. New bioinformatic approaches for extracting mechanistic ...

Dual-Branch Contrastive Network with Deep Separable Convolution for Enhanced 6mA Site Identification.

DNA N6-methyladenine (6mA) is a pivotal DNA modification integral to various biological processes, yet its exact regulatory role in eukaryotes is stil...

CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RN...

Characterizing DNA Origami Nanostructures in TEM Images Using Convolutional Neural Networks.

Artificial intelligence (AI) models remain an emerging strategy to accelerate materials design and development. We demonstrate that CNN models can cha...

A Hyperbolic Discrete Diffusion 3D RNA Inverse Folding Model for Functional RNA Design.

Generative design of functional RNAs presents revolutionary opportunities for diverse RNA-based biotechnologies and biomedical applications. To this e...

Predicting Biological Activity from Biosynthetic Gene Clusters Using Neural Networks.

Microorganisms such as bacteria and fungi have been used for natural products that translate to drugs. However, assessing the bioactivity of extract f...

CircFormerMoE: An End-to-End Deep Learning Framework for Circular RNA Splice Site Detection and Pairing in Plant Genomes

Circular RNAs (circRNAs) are important components of the non-coding RNA regulatory network. Previous circRNA identification primarily relies on high...

Enhancing Parameter Control Policies with State Information

Parameter control and dynamic algorithm configuration study how to dynamically choose suitable configurations of a parametrized algorithm during the...

AMRScan: A hybrid R and Nextflow toolkit for rapid antimicrobial resistance gene detection from sequencing data

AMRScan is a hybrid bioinformatics toolkit implemented in both R and [Nextflow](https://www.nextflow.io/) for the rapid and reproducible detection o...

HybridQC: Machine Learning-Augmented Quality Control for Single-Cell RNA-seq Data

HybridQC is an R package that streamlines quality control (QC) of single-cell RNA sequencing (scRNA-seq) data by combining traditional threshold-bas...

Sparse Autoencoders Reveal Interpretable Structure in Small Gene Language Models

Sparse autoencoders (SAEs) have recently emerged as a powerful tool for interpreting the internal representations of large language models (LLMs), r...

Mix-Geneformer: Unified Representation Learning for Human and Mouse scRNA-seq Data

Single-cell RNA sequencing (scRNA-seq) enables single-cell transcriptomic profiling, revealing cellular heterogeneity and rare populations. Recent d...

Topological Sequence Analysis of Genomes: Category Approaches

Sequence data, such as DNA, RNA, and protein sequences, exhibit intricate, multi-scale structures that pose significant challenges for conventional ...

A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level

Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approach...

EXAONE Path 2.0: Pathology Foundation Model with End-to-End Supervision

In digital pathology, whole-slide images (WSIs) are often difficult to handle due to their gigapixel scale, so most approaches train patch encoders ...

Expanding biobank pharmacogenomics through machine learning calls of structural variation.

Biobanks linking genetic data with clinical health records provide exciting opportunities for pharmacogenomic (PGx) research on genetic variation and ...

Predicting rare DNA conformations via dynamical graphical models: a case study of the B→A transition.

DNA exhibits local conformational preferences that affect its ability to adopt biologically relevant conformations, such as those required for binding...

Multi-Disease Deep Learning Framework for GWAS: Beyond Feature Selection Constraints

Traditional GWAS has advanced our understanding of complex diseases but often misses nonlinear genetic interactions. Deep learning offers new opport...

Bridging KAN and MLP: MJKAN, a Hybrid Architecture with Both Efficiency and Expressiveness

Kolmogorov-Arnold Networks (KANs) have garnered attention for replacing fixed activation functions with learnable univariate functions, but they exh...