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A PLM-Based Method for Predicting Protein Ion Channel Modulators for Drug Discovery and Safety Evaluation

Ion channels are central to regulating neuronal communication, cardiac rhythm, and muscle contraction. Their modulation can induce therapeutic benefits but may also lead to adverse or toxic effects. This study presents IonNTXpred, a protein language model (PLM)-based method for predicting protein ion channel modulators, including channel-specific (Na□, K□, Ca²□, and others) and moonlighting protei...

XChrom: a cross-cell chromatin accessibility prediction model integrating genomic sequence and cellular context

Single-cell chromatin accessibility offers unique insights into transcriptional regulation beyond gene expression. However, paired datasets of these two modalities remain relatively scarce, and existing computational models cannot simultaneously predict chromatin accessibility for unseen genomic regions and cells. Here, we present XChrom, a deep learning framework for genome-wide cross-cell chroma...

BiosInt: Biosensor-based smart design of pathway dynamic regulation for industrial biomanufacturing

Industrial-scale production of bio-based chemicals in the circular green bioeconomy still faces inefficiencies arising from scaling up challenges. Bio...

Using Large Language Models to Assemble, Audit, and Prioritize the Therapeutic Landscape

We present an AI-assisted pipeline for disease-specific drug landscape analysis. Given a disease name, the system assembles a comprehensive, evidence-...

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorpo...

TSProm: Deciphering the Genomic Context of Tissue Specificity

Characterizing tissue-specific (TSp) gene expression is crucial for understanding development and disease; however, traditional expression-based metho...

Generative Design of Cell Type-Specific RNA Splicing Elements for Programmable Gene Regulation

Programmable control of gene expression in specific cell types is essential for both basic discovery and therapeutic intervention, yet current strateg...

Integrative metabolome-genome analysis reveals the genetic architecture of metabolic diversity in sorghum grain

Cereal grains are fundamental to global food security and bioenergy production, yet the genetic and molecular bases of grain metabolic diversity remai...

Foundation model reveals the shared organization of transcription and topologically associating domains

The three-dimensional organization of chromatin into topologically associating domains (TADs) may impact gene regulation by bringing distant genes int...

Identification of SASP-associated biomarkers and regulatory mechanisms in diabetic foot ulcers based on transcriptomics and experimental validation

Diabetic foot ulcers (DFU) constitute a major complication arising from diabetes mellitus. Emerging research findings have underscored the pivotal con...

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

Adults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neuro...

Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Over 100 genes have been implicated in congenital heart disease (CHD), yet the genetic basis for >50% of CHD remains unexplained. A key challenge is t...

Protocol for the development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data

Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical be...

Characterisation of 3000 patient reported outcomes with predictive machine learning to develop a scientific platform to study fatigue in Inflammatory Bowel Disease

Fatigue is commonly identified by IBD patients as major issue that affects their wellbeing. This presentation, however, is complex, multifactorial and...

Prospective Blinded evaluation of Thermalytix, an artificial intelligence-enhanced breast thermal imaging software, correlated with radiologist-interpreted mammograms: Results of an exploratory study in Zambia

While mammography is commonly used for breast cancer detection, its widespread implementation in resource-constrained nations is challenging. Artifici...

AI regulation in healthcare around the world: what is the status quo?

The rapid adoption of artificial intelligence (AI) raises challenges related to ethics, safety, equity, and governance that require robust regulatory ...

How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations

The recent proliferation of AI-enabled medical devices and the growing emphasis on clinical translation creates a critical need to understand the evol...

Synthesizing evidence regarding artificial intelligence generated radiological reports based on medical images: a scoping review protocol

Considering numerous radiological images and the heavy workload of writing corresponding reports in clinical work, it is significant to leverage artif...

PREACT-digital: Study protocol for a longitudinal, observational multi-center study on wearable- and EMA- based predictors of non-response to CBT for internalizing disorders

Despite CBT’s status as a first-line treatment, a substantial proportion of patients does not experience sufficient symptom relief. Recent advances in...

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