Qian Cheng
@sgqcheng
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Senior Editor @NatureComms. PhD @Cambridge_Uni. Views my own.
London, England
Joined September 2010
The @NatureConf on AI-Augmented Biology is open for registration! We will explore how artificial intelligence is transforming the life sciences. 📅 October 22-24 2025 | 📍 Nanjing, China @NJU1902 @Nature @NatureComms @NatureBiotech @naturemethods
https://t.co/AppgHgYbs4
natureconferences.streamgo.live
Organised by Nanjing University，Nature, Nature Communications, Nature Biotechnology, Nature Methods The Nature conference on "AI Augmented Biology" explores how the integration of artificial intell...
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A graph neural network-based model trained on historical relative abundance data predicts species abundance dynamics for weeks to months for any longitudinal microbial dataset. @kasperskytte
@NatureComms
#BiotechNatureComms
https://t.co/CbMr9E0Gfa
nature.com
Nature Communications - Reliable prediction of bacterial abundance dynamics in microbial communities is still unresolved. Here, the authors built a graph neural network-based model trained on...
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Benchmarking scHi-C embedding methods shows that data representation, preprocessing options, and biological settings play a more important role in identifying cell states. @FulaiJin
@NatureComms
#BiotechNatureComms
https://t.co/YyTiPpje55
nature.com
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...
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SpatialMETA is a conditional variational autoencoder-based framework designed for the integration of spatial transcriptomics and metabolomics data. @wanluliu
#BiotechNatureComms
#SpatialOmics
#Metabolomics
https://t.co/qkQ8a1OeTG
nature.com
Nature Communications - Simultaneous profiling of spatial transcriptomics (ST) and metabolomics (SM) offers a novel way to decode tissue microenvironment heterogeneity. Here, the authors present...
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A causal framework HALO examines epigenetic plasticity and gene regulation dynamics in single-cell multi-omic data. #Chromatin_accessibility #BiotechNatureComms @NatureComms
https://t.co/RbfDgqgSYB
nature.com
Nature Communications - Chromatin accessibility dynamics causally influence changes in gene expression levels, but these fluctuations may not be directly coupled over time. Here, authors develop...
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.@apsduk @uniofwarwick use a host-aware modelling framework to develop genetic controllers to sustain synthetic gene expression. @NatureComms
#synbio #engbio #BiotechNatureComms
https://t.co/vmZLJmA2cX
nature.com
Nature Communications - Engineered gene circuits often degrade over time due to mutation and selection. Here the authors use a host-aware modelling framework to develop genetic controllers to...
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A #machinelearning strategy to predict the impact of metabolic gene deletions, offering high accuracy for gene essentiality across varied organisms and for many other phenotypes. @NatureComms
@doyarzunrod
#syntheticbiology
#BiotechNatureComms
https://t.co/eEA7kym7Nu
nature.com
Nature Communications - Gene deletions alter cellular physiology in complex and poorly understood ways. Here, authors present a machine learning strategy to predict the impact of metabolic gene...
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mcRigor detects and filters heterogeneous metacells, optimises metacell partitioning, and improves reliability in single-cell omics studies @NatureComms
@jsb_ucla
#BiotechNatureComms
nature.com
Nature Communications - Aggregating similar single cells into metacells is a common heuristic for sparse data, but risks mixing dissimilar cells. Here, authors present mcRigor, which detects and...
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Three commercially available spatial transcriptomics approaches (CosMx, MERFISH, and Xenium) are assessed for immune profiling of solid tumours. @kchenken
@NatureComms
#BiotechNatureComms #SpatialTranscriptome
https://t.co/fsuSAaukVv
nature.com
Nature Communications - Spatial cell distribution within a tissue microenvironment is a rapidly advancing field. Here, authors assess three commercially available single-cell resolution spatial...
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CLADES unveils clonal cell fate and differentiation dynamics in human cord blood and adult mouse haematopoiesis. @YuanhuaHuang
@MingzeGao2
#BiotechNatureComms
https://t.co/mglx99VQ3J
nature.com
Nature Communications - Recent studies have traced haematopoiesis at the clonal level but lack a way to extract dynamical information. Here, authors develop CLADES, a tool to estimate cellular...
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GrID-Net links noncoding variants to genes by exploiting the time lag between epigenomic and transcriptional cell states. @rohitsingh8080
@lab_berger
@alexpywu
#BiotechNatureComms
https://t.co/HPVXLSwr4E
nature.com
Nature Communications - Single-cell multimodal data has the potential to unveil noncoding disease mechanisms. Here, authors introduce GrID-Net, a graph-based Granger causal approach that links...
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MELISSA quantifies integration site risks and clone growth effects, aiding the safety evaluation of therapies in both research and clinical settings. @NatureComms
#viral_vector_integration #BiotechNatureComms
https://t.co/9mEintPRJE
nature.com
Nature Communications - Viral vector integration can affect the safety of gene and cell therapies. Here, authors introduce MELISSA, a regression-based statistical tool that quantifies integration...
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A scalable model DECIPHER learns disentangled cellular embeddings in large-scale heterogeneous spatial omics data. @NatureComms
@xiachenrui2000
@ZhiJieCaoZJ
@gao_laboratory
#BiotechNatureComms
https://t.co/37ZBQt6YYh
nature.com
Nature Communications - Cell function depends on both its molecular identity and spatial context, but these are often hard to disentangle. Here, authors present DECIPHER, a scalable deep learning...
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A multi-scale, multi-context, and interpretable mapping strategy to map cells across space, time, and disease. @KJWonKJ
#spatialMapping
#spatialOmics
#BiotechNatureComms
https://t.co/4AHX2S23ez
nature.com
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...
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TrimNN identifies conserved cellular community motifs, revealing links between spatially distributed cell patterns and diverse phenotypes. @Yang__fish
@ShuangWang0
@QinMaBMBL
@DongXu10710609
@juexinwang
#BiotechNatureComms
https://t.co/NTfwKgytP1
nature.com
Nature Communications - Cellular spatial organisation is crucial for shaping tissue functions and phenotypes. Here, authors present TrimNN, a graph-based deep learning framework to identify...
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Using microfluidics and endogenous reporters, single cells are tracked to reveal how temporal dosing rewires chromatin in a model with near single-cell accuracy. @StevenWSmeal
#BiotechNatureComms
https://t.co/IWHx8d01Zw
nature.com
Nature Communications - Cells rely on limited numbers of transmembrane receptors to process signals from dynamic microenvironments. Using microfluidics and endogenous reporters, the authors track...
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Topology for revealing fundamental organising features of the protein universe, providing insights into domain architecture, binding sites, evolution, and disease. @NatureComms
https://t.co/RB5J3cOisn
nature.com
Nature Communications - Deep learning enables large-scale protein structure prediction, yet linking structure to function remains a challenge. Here, the authors use topology to reveal fundamental...
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CausCell: a causal disentanglement framework that generates explainable, generalisable, and controllable representations for #singlecell omics data. @greysonc98
@Kejing_Dong #BiotechNatureComms
https://t.co/6ZFktOxT15
nature.com
Nature Communications - Single-cell omics data contain complex, entangled biological signals that challenge interpretation. Here, authors present CausCell, a causal disentanglement framework that...
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A computational framework for single cell and spatial alternative splicing analysis with Nanopore long read sequencing @NancyZh60672287
#BiotechNatureComms
https://t.co/mVlM98zeqf
nature.com
Nature Communications - Single-cell isoform quantification using Nanopore long reads remains limited by sequencing errors. Here, authors present Longcell, a computational framework that corrects...
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Bering performs joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings @Kang_Jin__
@JianShuLab
#BiotechNatureComms
https://t.co/rbRDjhqzJq
nature.com
Nature Communications - Cell segmentation remains a great challenge in high-resolution spatial-omics data. Here, the authors introduce a graph-based deep learning model that exploits transcript...
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A computational tool #SCALPEL for #isoform quantification at the single-cell level using 3’ scRNA-seq data @miriplass @PlassLab #BiotechNatureComms
https://t.co/Oz6VkQTLtN
nature.com
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...
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