Work Force

H3BERTa: A CDR-H3 specific language model for antibody repertoire analysis

Antibodies are central to immune defense and therapeutic design, yet predicting which sequences confer functional activity remains challenging. Deep learning models trained on full variable regions often struggle due to sparse experimental data, signal dilution from conserved framework residues, and the extreme diversity of hypervariable loops. The heavy-chain complementarity-determining region 3 ...

Assessing Scale and Predictive Diversity in Models for Single-Cell Transcriptomics based on Geneformer

Foundation models are increasingly applied to single-cell transcriptomics, where they promise to capture generalizable representations that support diverse downstream analyzes. However, two central questions remain: Does scaling pre-training data reliably improve performance, and do models trained on rank-ordered expression profiles confer advantages for mitigating batch effects? We addressed thes...

The Macroevolution of Filamentation Morphology Across the Saccharomycotina Yeast Subphylum

Saccharomycotina yeasts are a highly diverse and widely distributed subphylum of ascomycete fungi that exhibit diversity in their asexual growth morph...

Rubisco is slow across the tree of life

Rubisco is the main gateway through which inorganic carbon enters the biosphere, catalyzing the vast majority of carbon fixation on Earth. This pivota...

Examining Selection Dynamics and Limitations in Multi-round Protein Selection of High Diversity Libraries

Proteins and peptides underpin essential biological functions and technological applications, from targeting disease-relevant interactions to providin...

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...

Closing the Sim-to-Real Gap: An End-to-End Robotic Ultrasound System Leveraging In Vivo Reinforcement Learning and 3D-Prior Guided Hybrid Control

Abdominal ultrasound is a crucial first-line diagnostic tool, yet its efficacy is inherently constrained by a strong dependency on operator skill, lea...

Ensembles of Graph Neural Networks Supervised by Genotype-to-Phenotype Structures Improved Genomic Prediction Performance

Accurate selection of favourable crop genotypes has motivated the exploration of diverse prediction algorithms for crop breeding applications. One gen...

MeLSI: Metric Learning for Statistical Inference in Microbiome Community Composition Analysis

Microbiome beta diversity analysis relies on distance-based methods including PERMANOVA combined with fixed ecological distance metrics (Bray-Curtis, ...

A dataset of differentiable biologically-derived single neuron models

Biological neural networks contain diverse cell types with heterogeneous electrophysiological properties. Artificial neural networks (ANNs) model comp...

Benchmarking And Datasets For Ambient Clinical Documentation: A Scoping Review Of Existing Frameworks And Metrics For AI-Assisted Medical Note Generation

The increasing adoption of ambient artificial intelligence (AI) scribes in healthcare has created an urgent need for robust evaluation frameworks to a...

Efficient and Secure µ-Training and µ-Fine-Tuning for TinyML Optimization and Personalization at the Edge

This study introduces a novel approach for training and fine-tuning machine learning models for bio-signal data analysis on edge medical devices. The ...

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health Records

Electronic health records (EHRs) contain multimodal data that can inform diagnostic and prognostic clinical decisions but are often unsuited for advan...

Comparative Medical Ecology of Gut Microbiomes in Major Neurodegenerative, Neurodevelopmental, and Psychiatric (NNP) Disorders

This study provides a comprehensive medical ecology analysis of gut microbiome alterations in four neuropsychiatric disorders: Alzheimer’s disease (AD...

OphthUS-GPT: Multimodal AI for Automated Reporting in Ophthalmic B-Scan Ultrasound

The rapid advancement of AI in ophthalmology is transforming diagnostics, especially in resource-limited settings. The shortage of ophthalmologists an...

Interethnic Validation of Artificial Intelligence for prediction of Atrial Fibrillation Using Sinus Rhythm Electrocardiogram

Previous research has demonstrated acceptable diagnostic accuracy of AI-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation for predictin...

Evaluating Enhanced LLMs for Precise Mental Health Diagnosis from Clinical Notes

Anxiety, depression, and other mental health conditions are affecting millions of people worldwide each year. However, limited access to mental health...

Comprehensive Evaluation of Human Donor Liver Viability with Polarization-Sensitive Optical Coherence Tomography

Human liver transplantation is severely constrained by a critical shortage of donor livers, with approximately one quarter of patients on the waiting ...

Deep Learning Analysis of Figure Copying Tasks for Parkinson’s Disease Detection with GAN-Based Data Augmentation

Early and accurate diagnosis of Parkinson’s disease (PD) is essential for enabling timely treatment and effective disease management. In this study, w...

Development and Clinical Application of a Deep Learning-Based Endometrial Cancer Cytology Supporting Model

The global rise in endometrial cancer, including in Japan, and the shortage of pathologists and cytotechnologists has increased the diagnostic burden,...