Learning the language of protein-protein interactions - Nature Communications

Protein language models capture single proteins but struggle with interactions. Here, authors present MINT, trained on large PPI datasets, which outperforms existing PLMs in predicting binding, mutati...

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Designing molecular RNA switches with Restricted Boltzmann machines - Nature Communications

Riboswitches are allosteric RNA molecules that change conformation upon ligand binding to regulate downstream genes. Here, the authors use Restricted Boltzmann machines trained on natural sequences to...

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What is an Article in Press?

What is an Article in Press? How is the Article in Press different to the VoR?  Is the Article in Press citable?  How does indexing work with an Article in Press?  Can corrections/ amendments be m...

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PyFuRNAce: an integrated design engine for RNA origami - Nature Communications

RNA nanotechnology creates structural and functional RNA architectures for biomedicine, synthetic biology and beyond. Here, the authors introduce pyFuRNAce, an intuitive browser-based RNA design tool....

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Enhanced spatial clustering of single-molecule localizations with graph neural networks - Nature Communications

Single-molecule localisation microscopy enables nanoscale mapping of molecular organisation, but clustering stochastic data remains challenging. Here, authors present a graph neural network method tha...

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A comprehensive benchmark of single-cell Hi-C embedding tools - Nature Communications

Embedding is a key step in single-cell Hi-C analysis to identify cell states. Here, the authors benchmark 13 embedding methods in 10 scHi-C datasets. They find that data representation, preprocessing ...

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IceQream: Quantitative chromosome accessibility analysis using physical TF models - Nature Communications

Cis regulatory elements endow genomes with sequence-encoded logic to drive cellular differentiation. Here, the authors introduce a biophysically principled sequence model that characterises complex TF...

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Multi-scale and multi-context interpretable mapping of cell states across heterogeneous spatial samples - Nature Communications

The alignment of heterogeneous spatial samples has become a growing challenge. Here, authors present a multi-scale, multi-context, and interpretable mapping strategy to map cells across space, time, a...

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Time-varying stimuli that prolong IKK activation promote nuclear remodeling and mechanistic switching of NF-κB dynamics - Nature Communications

Cells rely on limited numbers of transmembrane receptors to process signals from dynamic microenvironments. Using microfluidics and endogenous reporters, the authors track single cells to reveal how t...

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Single cell and spatial alternative splicing analysis with Nanopore long read sequencing - Nature Communications

Single-cell isoform quantification using Nanopore long reads remains limited by sequencing errors. Here, authors present Longcell, a computational framework that corrects these errors and uncovers spl...

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Quantification of transcript isoforms at the single-cell level using SCALPEL - Nature Communications

Single-cell RNA-seq facilitates the study of transcriptome diversity in individual cells. Here, authors introduce a tool for isoform quantification at the single-cell level using 3’ scRNA-seq data, co...

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Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis - Nature Communications

Activity recognition in live-cell imaging is laborious. Here, authors present, IVEA, a fully automated AI ImageJ plugin, that efficiently detects and classifies exocytosis events, from synaptic transm...

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ToxACoL: an endpoint-aware and task-focused compound representation learning paradigm for acute toxicity assessment - Nature Communications

Multi-species acute systemic toxicity assessment is fundamental for chemical classification, labelling and risk management. Here, the authors propose a machine learning paradigm, Adjoint Correlation L...

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Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values - Nature Communications

Individual data types in a single cell multi-omic assay are often processed and clustered independently before combined for further analysis. Here, authors showed that binarized gene expression d...

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GPerturb: Gaussian process modelling of single-cell perturbation data - Nature Communications

Single-cell CRISPR screens enable high-throughput analysis of how genetic changes affect individual cells. Here, authors present GPerturb, a method that accurately detects and quantifies gene-level ef...

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Modeling heterogeneous signaling dynamics of macrophages reveals principles of information transmission in stimulus responses - Nature Communications

To develop virtual cells, mathematical models must account for the heterogeneity of single cells. Here, authors develop virtual single cell NFκB signalling networks that recapitulate heterogenous expe...

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Ding Lab

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junding.lab.mcgill.ca

Automated cell annotation and classification on histopathology for spatial biomarker discovery - Nature Communications

Histopathology is essential for diagnosing cancer, but cell annotation remains unreliable and inefficient. Here, authors develop a method using deep learning and immune-fluorescence-guided cell labell...

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Cell Marker Accordion: interpretable single-cell and spatial omics annotation in health and disease - Nature Communications

Accurate cell type annotation is a major challenge in single-cell and spatial omics. Here, authors present a user-friendly platform providing robust automatic annotation and enhanced biological interp...

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Accelerating cell culture media development using Bayesian optimization-based iterative experimental design - Nature Communications

Optimising operational conditions for biological systems is a complex task. Here, authors present a Bayesian optimisation-based iterative experimental design framework that integrates data generation,...

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Mapping the nuclear landscape with multiplexed super-resolution fluorescence microscopy - Nature Communications

The cell nucleus coordinates diverse functions. Here, the authors utilise multiplexed super-resolution imaging to study how nuclear proteins are distributed relative to each other from the micro to th...

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Associate or Senior Editor, Nature Reviews Electrical Engineering

Job title: Associate or Senior Editor, Nature Reviews Electrical Engineering Location: Shanghai or New York – hybrid working model Closing date: 1st July 2025 About Springer Nature Group Springer Natu...

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A versatile information retrieval framework for evaluating profile strength and similarity - Nature Communications

Profiling assays measure thousands of features to uncover biological insights but lack reliable methods for quality evaluation. Here, the authors develop a versatile information retrieval framework to...

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An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates - Nature Communications

Mitophagy is crucial for mitochondrial function and is implicated in Alzheimer’s disease. Here, the authors introduce an AI-assisted fluorescence microscopy system to track mitophagic intermediates in...

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CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells - Nature Communications

Single-cell sequencing reveals cellular heterogeneity but is challenged by technical noise and batch effects. Here, authors present CellFM, an 800-million-parameter foundation model trained on 100 mil...

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Learning tissue representation by identification of persistent local patterns in spatial omics data - Nature Communications

Spatial omics reveal tissue structures and can aid patient stratification. The authors present a method to identify patterns in tissue patches, enabling analysis of disease progression and treatment r...

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Green Laboratory

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EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals - Nature Communications

Despite having structures for most proteins, we still do not know their function. Here, authors introduce EvoWeaver, a de novo method to identify genes working together using evolutionary information....

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scPRINT: pre-training on 50 million cells allows robust gene network predictions - Nature Communications

Authors present a state-of-the-art cell foundation model trained on 50 million cells. They show that the model generates a meaningful gene network and has zero-shot ability in various tasks.

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