Qian Cheng

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...

A computational framework for single cell and spatial alternative splicing analysis with Nanopore long read sequencing

@nancyrzhang.bsky.social
#BiotechNatureComms

www.nature.com/articles/s41...

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...

A computational tool #SCALPEL for #isoform quantification at the single-cell level using 3’ scRNA-seq data @franzake.bsky.social @mireyaplass.bsky.social #BiotechNatureComms

doi.org/10.1038/s414...

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...

A fully automated AI ImageJ plugin that detects and classifies #exocytosis events from synaptic transmission to single-vesicle fusion. @alishaib.bsky.social #BiotechNatureComms

doi.org/10.1038/s414...

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...

ToxACoL is an endpoint-aware and task-focused compound representation learning paradigm for #Acute_Toxicity_Assessment #BiotechNatureComms

doi.org/10.1038/s414...

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...

Binarized gene expression data can be concatenated with chromatin accessibility data for effective and integrated cell clustering @zhengdy.bsky.social @einsteinmededu.bsky.social #BiotechNatureComms

doi.org/10.1038/s414...

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...

GPerturb detects and quantifies gene-level effects of perturbations, with uncertainty estimates, revealing complex biological interactions. @cwcyau.bsky.social

doi.org/10.1038/s414...

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...

A virtual single-cell NFκB signalling networks that recapitulate heterogenous experimental stimulus-response dynamics @xiaoluguo.bsky.social #BiotechNatureComms

doi.org/10.1038/s414...

DOLPHIN: a deep learning method that enables exon- and junction-level analysis to improve cell representation and detect alternative #splicing. Ding Lab junding.lab.mcgill.ca #BiotechNatureComms

doi.org/10.1038/s414...

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...

A deep learning and immune-fluorescence-guided cell labelling method for accurate cell pattern identification. #BiotechNatureComms

doi.org/10.1038/s414...

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...

Cell Marker Accordion is a user-friendly platform providing robust automatic cell annotation of #single_cell and spatial populations @rdds-lab.bsky.social #BiotechNatureComms

doi.org/10.1038/s414...

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,...

A Bayesian optimisation-based iterative experimental design framework that integrates data generation, modelling, and optimisation to accelerate cell culture media development #BiotechNatureComms

doi.org/10.1038/s414...

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...

A multiplexed super-resolution imaging protocol studies how nuclear proteins are distributed relative to each other from the micro to the nanoscale. #BiotechNatureComms

doi.org/10.1038/s414...

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...

My first task is to hire an Associate/Senior Editor for @natrevelectreng.nature.com. Would you be interested in joining me to shape the journal? Pls DM me if you have any questions💡Apply by 1 Jul.
@natureportfolio.nature.com @springernature.com
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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...

A versatile information retrieval framework to quantify sample activity and similarity in large-scale profiling data @natcomms.nature.com @alxndrkalinin.bsky.social @shantanu-singh.cc @drannecarpenter.bsky.social

www.nature.com/articles/s41...

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...

An AI-assisted fluorescence microscopy system to track mitophagic intermediates in live cells @natcomms.nature.com

www.nature.com/articles/s41...

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...

CellFM: A 800-million-parameter foundation model pre-trained on transcriptomics of 100 million human cells. #BiotechNatureComms @natcomms.nature.com

www.nature.com/articles/s41...

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...

Kasumi identifies local patterns in tissue patches in spatial omics data @tanevski.bsky.social, @saezlab.bsky.social #BiotechNatureComms

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Green Laboratory Visit the post for more.

A data-efficient, generative AI-based toolkit for designing a diverse set of RNA molecules. #BiotechNatureComms

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alexgreenlab.org

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....

EvoWeaver identifies genes working together using evolutionary information and infers protein functions using only genomic sequences. @ahl27.bsky.social @natcomms.nature.com
www.nature.com/articles/s41...

.@jkobject.com @cantinilab.bsky.social @gabrielpeyre.bsky.social present a foundation model trained on 50 million cells, generating a meaningful gene network with zero-shot ability. #AIxBio @natcomms.nature.com

www.nature.com/articles/s41...

MSFragger-DDA+ enhances peptide identification sensitivity with full isolation window search - Nature Communications Proteomics often misses co-fragmented peptides in DDA data. Here, the authors introduce MSFragger-DDA+, a database search tool that enhances peptide identification by searching the full isolation wind...

MSFragger-DDA+ is a database search tool that enhances peptide identification by searching the full isolation window. #Proteomics @fcyucn.bsky.social @nesvilab.bsky.social

www.nature.com/articles/s41...

Statistical analysis of spatial patterns in tumor microenvironment images - Nature Communications Immunotherapy is transforming cancer treatment, with immune cell distribution in the tumour microenvironment key to predicting outcomes. Here, authors provide a robust framework to analyse spatial pat...

Authors @biaunit.bsky.socia provide a robust framework to analyse spatial patterns within the tumour microenvironment. @naturecomms.bsky.social
#spatiopath #immunotherapy #Cancer #TME

www.nature.com/articles/s41...

Computation-aided designs enable developing auxotrophic metabolic sensors for wide-range glyoxylate and glycolate detection - Nature Communications Auxotrophic metabolic sensors (AMS) are vital for bioengineering but are often time-consuming to develop. Here, the authors present a workflow for designing versatile AMS, demonstrating their use for ...

📑📑📑#synthetic_biology @eorsi.bsky.social @pabnik.bsky.social present a workflow for designing versatile auxotrophic metabolic sensors for glyoxylate and glycolate detection @naturecomms.bsky.social
www.nature.com/articles/s41...

DNA-Based Computing and Data Storage This cross-journal Collection shines a spotlight on research exploring DNA as a scalable and sustainable medium for computing and data storage.

🧬💻Call for papers: DNA-based Computing and Data Storage

@naturecomms.bsky.social @commsbio.bsky.social @commseng.bsky.social
@natureportfolio.nature.com

The deadline is mid September 2025. Feel free to drop me a message if you want to discuss submissions.

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Please take a look at the Springer Nature’s Opening Doors Internship Programme. It's open for applications in the UK, US and Germany as well as China and the Netherlands. The deadline is 14 March (28 February UK). Explore the available positions here:
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FusOn-pLM: a fusion oncoprotein-specific language model via adjusted rate masking - Nature Communications Fusion oncoproteins drive paediatric cancers but are challenging to target due to their intrinsic disorder and lack of druggable pockets. Here, authors present FusOn-pLM, trained on FusOn-DB, which us...

@pranam.bsky.social  present FusOn-pLM, which uses dynamic masking to outperform baselines in fusion-specific tasks and predict drug-resistant mutations
#BiotechNatureComms

www.nature.com/articles/s41...

Qian Cheng, Ph.D. on LinkedIn: Computational and Theoretical Biology Overview of #January2025 #Computational_Biology Methods papers published in Nature Communications Nature Portfolio. (https://lnkd.in/ejMPmR-A) Jingyi Jessica…

Overview of some #Computational_Biology papers published in January 2025 in @naturecomms.bsky.social www.linkedin.com/posts/qian-c...

Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction - Nature Communications Identifying and characterizing secreted virulence proteins are fundamental for deciphering microbial pathogenicity. Here, the authors introduce a practical training framework to improve protein langua...

Authors introduce a practical training framework to improve protein language model representations by integrating biological features and prior information through contrastive learning. #BiotechNatureComms
www.nature.com/articles/s41...

Transcriptome size matters for single-cell RNA-seq normalization and bulk deconvolution - Nature Communications Existing cell type deconvolution methods, crucial for studying tumour environments, overlook some critical issues. Here, authors analyse how these issues impact on deconvolution and develop methods to...

.@jiyang_yu @StJudeResearch introduce new methods for cell type deconvolution and scRNA-seq data normalisation. #BiotechNatureComms
www.nature.com/articles/s41...

Spatial integration of multi-omics single-cell data with SIMO - Nature Communications Existing tools face limitations in integrating spatial data with single-cell multi-omics datasets. Here, authors introduce a computational tool that maps diverse single-cell modalities, including RNA,...

SIMO maps diverse single-cell modalities, including RNA, chromatin accessibility, and DNA methylation, onto spatial tissues. #BiotechNatureComms
www.nature.com/articles/s41...