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SPOWScience Paper of the Week Vol. 1 No. 3 2026-W37

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Single-Cell Atlas of Lineage States, Tumor Microenvironment, and Subtype-Specific Expression Programs in Gastric Cancer

Cancer Discovery CC BY 4.0

Why this paper

위암은 한국에서 발생률 상위 암이면서도 단일세포 지도가 늦게 나왔습니다. 이 논문은 계통 상태와 미세환경을 한 코호트에서 함께 봅니다. 폐암 두 호를 읽은 독자가 다른 장기로 건너가 보는 자리로 알맞습니다.

Original Korean For high school For executives
Open in the IDEPublisherRaw data

The courses that make this paper readable

12 courses · 240 lessons
Where are you coming from? If you come from computer science11 If you come from biology5 If you come from the bench5 The shortest road11 If you have to decide something3

You have done the experiments; now you want to read the data.

  1. 1 Algorithms 20강 · 필수
  2. 2 Bioinformatics 20강 · 필수
  3. 3 tcell 20강 · 필수
  4. 4 traffic 20강 · 필수
  5. 5 tcrhla 20강 · 필수

This order is computed from what the paper needs and how the courses depend on one another — change the paper and the order changes with it.

Run it
Reading box

768 MB · 1 core. The four editions and a cut-down notebook — real scanpy code on a 2,000-cell subsample, done in 30 seconds.

Reproduction box

8 GB · 4 cores, the scanpy stack installed and the raw data mounted at /data. It costs, so it sleeps after 10 idle minutes — your files stay.

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Lessons that share this paper's vocabulary
  1. /stat 9강 p 값 — 무엇을 말하고 무엇을 말하지 않나 CD38
  2. /stat 15강 FDR — 몇 개가 틀려도 괜찮다고 정하는 것 CD38
  3. /arac 11강 관용값 — DPI 가 저지르는 실수 CD38
  4. /dataset 9강 크기를 맞춘다 — 정규화 없이는 아무것도 비교할 수 없다 CD38
  5. /spatial 11강 행렬이 만들어지는 순간 — 여기서 단일세포와 만난다 CD38
  6. /mirna 9강 씨앗 — miRNA 가 표적을 고르는 일곱 글자 위암
  7. /mirna 12강 내 결과 대 TargetScan — 516 과 436 위암
  8. /celltx 18강 값 — 듣는 약과 닿는 약은 다르다 CD38
  9. /innate 20강 정리 — 선천면역이 정하는 것 CD38
  10. /bcell 8강 배중심 — 몸 안에서 진화가 일어나는 유일한 자리 CD38
1 Operating Systems 20강 2 Computer Architecture 20강 3 Networks 20강 4 Domain Management 20강 5 Data Structures 20강 6 Algorithms 20강 7 Databases 20강 8 Security 20강 9 Discrete Math 20강 10 Python 20강 11 Chemistry 20강 12 Bioinformatics 20강 13 Linear Algebra 20강 14 Probability & Statistics 20강 15 Machine Learning 20강 16 Deep Learning 20강 17 VIPER 20강 18 DIGGIT 20강 19 Gene Hunt 20강 20 ARACNe 20강 21 Bioinfo Datasets 20강 22 Spatial 22강 23 miRNA-mRNA 20강 24 Bulk RNA-seq 20강 25 tcell 20강 26 antigen 20강 27 checkpoint 20강 28 Cell Therapy 20강 29 innate 20강 30 bcell 20강 31 immunometab 20강 32 traffic 20강 33 escape 20강 34 myeloid 20강 35 cytokine 20강 36 immunology 20강 37 Immune Map 22강 38 TIL 20강 39 Digital Twin 20강 40 Lab Chemistry 20강 41 In Vivo 20강 42 Humanized Mice 20강 43 Pharmacokinetics 20강 44 Toxicology & GLP 20강 45 Clinical Trials 20강 46 Phase II/III & Approval 20강 47 Epidemiology 20강 48 Flow & Histology 20강 49 Cell Culture 20강 50 Perturbation 20강 51 Molecular Assays 20강 52 Library Prep 20강 53 Illumina Sequencers 20강 54 10x Genomics 20강 55 viz 20강 56 TCGA 20강 57 tmb 20강 58 tcrhla 13~17강 59 Perturb-seq 20강 60 insilico 20강 61 wrn 20강 62 pdrug 20강 63 Target Discovery 20강 64 geo 20강 65 sra 20강 66 als 20강 67 gwas 20강 68 Retracing the TNIK Discovery 20강 69 Somatic Mutation Databases 20강 70 In-Silico Target Discovery Practicum 20강 71 From Inverted Papilloma to Carcinoma 20강 72 Protein Structure Prediction 20강 73 Docking and Molecular Dynamics 20강 74 Personalised mRNA Cancer Vaccine 20강 75 Endosomal Escape 20강 76 Lymph Node 20강 77 Cytotoxic T Lymphocytes 20강 78 Canine Mast Cell Tumour I 20강 79 Canine Mast Cell Tumour II 20강 80 On-Demand mRNA Synthesiser I 20강 81 On-Demand mRNA Synthesiser II 20강 82 On-Demand mRNA Synthesiser III 20강 83 mRNA Synthesis Reagents 20강 84 mRNA Synthesiser Cost Analysis 20강 85 mRNA Synthesiser Mechanism 20강 86 mRNA Synthesiser Firmware 20강 87 mRNA Vaccine Design I 20강 88 mRNA Vaccine Design II 20강 89 mRNA Vaccine Design III 20강 90 mRNA Vaccine Design IV 20강 91 mRNA Vaccine Design V 20강 92 mRNA Vaccine Design VI 20강 93 mRNA Vaccine Design (Zheng) I 20강 94 mRNA Vaccine Design (Zheng) II 20강 95 mRNA Vaccine Design (Zheng) III 20강

The paper's methods, and where each is taught

14
Single-Cell Sequencing 📦 Sequencing Libraries, First Steps
Bioinformatic QC, Normalization, Clustering, and Differential Gene Expression of Single-Cell Data 🧬 Bioinformatics, First Steps
Bioinformatic QC, Normalization, Clustering, and Differential Gene Expression of Single-Cell Data 🧭 Algorithms, First Steps
Trajectory Analysis 🧭 Algorithms, First Steps
TCR Analysis 🤝 TCR-HLA and CD4/CD8, First Steps
Humanized Mouse Model 🐁 In Vivo Experiments, First Steps
Humanized Mouse Model 🩸 Humanized Mice, First Steps
Fibroblast Cell Culture Experiments 🧫 Cell Culture, First Steps
Fibroblast Cell Culture Experiments ⚔️ T Cells, First Steps
KLF2 Knockdown Model ✂️ Genetic Perturbation, First Steps
Western Blotting 🧷 Molecular Assays, First Steps
Transwell Migration Assay 🚚 Immune Trafficking, First Steps
Analysis of Bulk RNA-seq Data 📦 Sequencing Libraries, First Steps
Generation, Maintenance, and Single-Cell Sequencing of Gastric Cancer PDOs 📦 Sequencing Libraries, First Steps

Back issues

See all
2026-W40 Streamlined and on-demand preparation of mRNA products on a universal integrated platform Microsystems & Nanoengineering CC BY 4.0 2026-W39 In-Silico Drug discovery approach targeting receptor tyrosine kinase-like orphan receptor 1 for cancer treatment Scientific Reports CC BY 4.0 2026-W36 Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma Nature Communications CC BY 4.0 2026-W35 DDX54 downregulation enhances anti-PD1 therapy in immune-desert lung tumors with high tumor mutational burden PNAS 122(14) e2412310122 CC BY-NC-ND 4.0