董炜

PhD

[Zexian Zeng @ZexianZeng]

Where a cell resides can be as important as what genes it expresses. Our most recent Spatial CRISPR Screen work, a platform that enables high-resolution, large-scale spatial CRISPR screening while simultaneously profiling the whole transcriptome https://t.co/7s0axrNRhe

[Cancer Cell @Cancer_Cell]

Online Now: An epigenetic four-lane route to camouflage for cancer cells https://t.co/q1idyaE3Ge

[iMeta @iMetaScience]

🚀 Latest Good News！
iMeta achieves a new Impact Factor of 44.4！
⚡️iMeta (IF 44.4) ranks in the top 0.2% of journals worldwide (47/22,643)—submit your best research and join us in shaping the future of science! @WileyGlobal
https://t.co/wzLbm1Gw7W
#iMeta

[董炜 @dongwei1220]

Comprehensive Integrated Single‐Cell and Spatial Transcriptomics Unveil the Dynamic Landscape of Betel Nut‐Associated Oral Mucosal Carcinogenesis and Its Tumor Microenvironment - Dong - 2026 - MedComm - Wiley Online Library https://t.co/lU1PU0nnbS

[Rong Fan @RongFan8]

🤩 spatial panoramic in vivo CRISPR screen via Perturb-DBiT 🤩 Excited to share our collaborative work with @sidichen lab and many outstanding collaborators, now published in Nature Biotechnology!
https://t.co/swMT8pJajh

[Nature Biotechnology @NatureBiotech]

Large-scale, spatially resolved panoramic CRISPR screening in native tissue environments using Perturb-DBiT https://t.co/4ihbkqGeJO

[董炜 @dongwei1220]

Comprehensive Integrated Single‐Cell and Spatial Transcriptomics Unveil the Dynamic Landscape of Betel Nut‐Associated Oral Mucosal Carcinogenesis and Its Tumor Microenvironment - Dong - 2026 - MedComm - Wiley Online Library https://t.co/lU1PU0nnbS

[Rahul Satija @satijalab]

Our stream for Single Cell Genomics Day goes live tomorrow morning at https://t.co/KJpeGwWLIr , look forward to seeing you there for our 10th year!

[董炜 @dongwei1220]

HIV-1 infection converts CD4+ T cells to HLA class II–restricted CD8+ T cells | Science Translational Medicine https://t.co/IlgT0QslhX

[Dr. Gennadi Glinsky, MD, Ph.D. @gglinskii]

HIV-1 infection converts CD4+ T cells to HLA class II–restricted CD8+ T cells | Science Translational Medicine https://t.co/wZ4j8r6CP6

[董炜 @dongwei1220]

HIV-1 infection converts CD4+ T cells to HLA class II–restricted CD8+ T cells | Science Translational Medicine https://t.co/IlgT0QslhX

[Linghua Wang, MD, PhD @IamLinghua]

1/ Thrilled to share our new paper, out today in @ScienceMagazine! We built a pan-cancer spatial atlas of tertiary lymphoid structures (TLSs) and developed computation and AI frameworks to study TLS biology at scale.
https://t.co/zgcBnnm7Rl

[Nature Reviews Genetics @NatureRevGenet]

New online! Single-cell trimodal profiling with scHiCAR https://t.co/3zfuc8npBU

[iMeta @iMetaScience]

Navigating the future of nano‐pesticides: A perspective on design, efficacy, mechanisms, and environmental stewardship
🌱Nano-pesticides are reshaping crop protection toward sustainable agriculture.
https://t.co/zeT5XEpC8r

[NatureStructMolBiol @NatureSMB]

New online! Direct roles of long non-coding RNAs in transcription activation https://t.co/NW9GyZXvbk

[iMeta @iMetaScience]

Two stable gut microbiome guilds predict liver tumor class and treatment responses

⚙️ Functionally opposing microbial guilds highlight an ecological basis for tumor progression and clinical outcomes. #Hepatocellular @WileyHealth
https://t.co/QVa6EJm3wO

[Daniel Dan Liu @Daniel_D_Liu]

Traditional single cell transcriptomics doesn't capture most non-coding RNAs. In this work, led by @alinaisakovaSci and @StephenQuake, we introduce TotalX, a @10xGenomics-compatible pipeline that captures both coding and non-coding transcripts. Out now in @NatureBiotech! 1/7

[Jian Yang @jyang1981]

Excited to see our work in @Nature! We combined our PIGA workflow & a cost-effective sequencing strategy to build the 1000 Chinese Pangenome (1KCP). We hope this methodology & resource help unlock complex variants in human health. @wang_yifei @DuanZhongqu
https://t.co/OahSS9cZPZ

[Waggoner Lab @LabWaggoner]

CHARM enables integrative dissection of the three-dimensional epigenome at single-cell resolution, providing a versatile platform for decoding the regulatory landscape across diverse cells in complex tissues @Nature
https://t.co/AsEbTTXGN3

[Hao Yin @HaoYin20]

3d-OT
Spatial Multi-omics Alignment

Spatiotemporal reconstruction of🐭embryonic heart (+blood vessels) brain lung liver muscle (E11.5~16.5) kidney ovary (E11.5~12.5)

Geometry-aware, soft correspondence optimal transport-based
Chamfer Distance & Cell-Type Matching Index as performance metrics

👉Spatial domain identification
vs SEDR stLearn SpaGCN GAAEST STAGATE GraphST SpaNCMG

👉Spatial multi-omics domain
vs MISO CellCharter COSMOS SpatialGlue

👉Within-platform alignment
vs SLAT Harmony PASTE PASTE2 SANTO

👉Cross-platform alignment
SeqIF vs StereoSeq
Spatial CUT&Tag + RNA vs Spatial ATAC + RNA
vs SLAT Harmony PASTE

@naturemethods 2026
https://t.co/vbdDUwnuo5