Prescriptions

ARACoFusion: Uncertainty-aware calibrated deep learning for protein-protein interaction network prediction in Arabidopsis thaliana

Accurate mapping of the Arabidopsis thaliana protein-protein interaction (PPI) network is essential for deciphering complexity of plant systems biology. Here, we present ARACoFusion, a specialized deep learning architecture designed to predict inter-protein connectivity directly from primary sequences. To capture the asymmetric dependencies between plant proteins, the framework utilizes a reciproc...

RoadGIE: Towards A Global-Scale Aerial Benchmark for Generalizable Interactive Road Extraction

Accurate road segmentation from aerial imagery is fundamental to many geospatial applications. However, existing datasets often suffer from limited scene diversity, low semantic granularity, and poor structural continuity, restricting their generalization across environments. To address these challenges, we introduce WorldRoadSeg-360K, the largest and most diverse road segmentation dataset to date...

SpatialClaw: A Memory-Augmented Autonomous Ecosystem for Spatial Omics Analysis

While the expansion of spatial omics has revolutionized our ability to dissect tissue architecture, the accumulation of incompatible computational met...

DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking

Frontier LLMs now perform strongly across a wide range of physics evaluations, but it is hard to disentangle genuine reasoning from recall of establis...

Pixel-Level Pavement Distress Assessment Using Instance Segmentation

Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization ...

Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies

Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to de...

Spatio-temporal machine learning for multi-horizon prediction of bluetongue outbreaks

Reliable early warning of infectious disease outbreaks remains a major challenge for surveillance systems, particularly for vector-borne pathogens who...

Large-Scale Assessment of Animal-to-Human Drug Translation Using Natural Language Processing

Background: Large-scale estimates of animal-to-human drug translation and the study characteristics associated with successful translation remain limi...

Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies

Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to de...

Precision Physical Activity Prescription via Reinforcement Learning for Functional Actions

Physical activity (PA) plays an important role in maintaining and improving health. Daily steps have been a key PA measure that is easily accessible w...

Progeny differentiation in faba bean using hyperspectral images and machine learning

Though currently a minor crop, faba bean is a promising source of plant-based protein as global diets shift towards more plant-based nutrition. To rea...

geneML: Gene annotation across diverse fungal species using deep learning

Accurate gene prediction remains a major bottleneck in fungal genomics, where lineage diversity and alternative splicing challenge existing ab initio ...

Stereochemistry-Aware Drug-Target Affinity Prediction

Drug-target affinity (DTA) prediction is a key task in drug discovery, enabling the estimation of the interaction strength between candidate compounds...

Learning Chirality-Aware Representations to Predict Drug Side Effect Frequencies

Ab initio prediction of side effect frequencies is important for assessing the risk-benefit profile of drugs and for identifying potential adverse eff...

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval

E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This im...

EpiReasoner: An Integrated Artificial Intelligence Framework for Phenotype-to-Genotype Reasoning in Plant Epidermal Development

Achieving high-throughput and precise phenotypic quantification and imaging modalities of stomatal and epidermal cells across diverse species remains ...

Deep learning models for chemical perturbation prediction do not yet utilise drug molecular features

Recent deep learning models for L1000 chemical perturbation prediction incorporate dedicated drug molecular encoders. We retrained seven such models f...

Smartphone Placement Recognition during Walking: Performance Determinants and Real-World Generalizability

The opportunity to collect movement data from smartphones for prolonged periods has opened new perspectives in the field of clinical movement analysis...

Towards Fine-Grained and Verifiable Concept Bottleneck Models

Concept Bottleneck Models (CBMs) offer interpretable alternatives to black-box predictors by introducing human-relatable concepts before the final out...

Using Deep Learning Models of Gene Regulation to Guide Drug Prioritization

Drug repurposing offers a cost-effective strategy to accelerate therapeutic discovery, but most computational approaches fail to model noncoding genet...