README.md

metadata

title: K R&D Lab — Cancer Research Suite
short_description: Real‑time data integration for precision oncology
emoji: 🧬
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 5.22.0
python_version: '3.10'
app_file: app.py
pinned: false

K R&D Lab — Cancer Research Suite

Author: Oksana Kolisnyk | kosatiks-group.pp.ua DEMO Repo: github.com/TEZv/K-RnD-Lab-PHYLO-DEMO_03-2026 ORCID: 0009-0003-5780-2290 Generated: 2026-03-07

---

Overview

A Gradio-based research suite combining live cancer data APIs with educational simulation tools. Designed for researchers, ML engineers, and students working at the intersection of cancer biology, drug delivery, and precision oncology.

Two tab groups:

• Group A — Real Data Tools (5 + 1 tabs): Live APIs, real results, never hallucinated
• Group B — Learning Sandbox (5 tabs): Rule-based simulations, clearly labeled ⚠️ SIMULATED

---

File Structure

K-RnD-Lab/
├── app.py              # Main Gradio application (all 10 tabs + Lab Journal)
├── chatbot.py          # RAG chatbot module (sentence-transformers + FAISS)
├── requirements.txt    # Python dependencies
├── README.md           # This file
├── research_gaps.md    # Part 2: 10 underexplored research directions
├── learning_cases.md   # Part 3: 5 guided investigation cases
└── data_sources.md     # All API endpoints and data sources

Runtime-generated:

├── cache/              # API response cache (JSON, 24h TTL)
└── lab_journal.csv     # Auto-logged research journal

---

Quick Start

Local

# 1. Clone
git clone https://github.com/TEZv/K-RnD-Lab-PHYLO-DEMO_03-2026
cd K-RnD-Lab-PHYLO-DEMO_03-2026

# 2. Install dependencies
pip install -r requirements.txt

# 3. Run
python app.py
# → Opens at http://localhost:7860

HuggingFace Spaces

1. Create a new Space: Gradio SDK, Python 3.10+
2. Upload app.py, chatbot.py, requirements.txt
3. Space auto-deploys — no secrets or API keys needed

The RAG chatbot downloads the all-MiniLM-L6-v2 model (~80 MB) on first run. Subsequent runs use the HF cache. Allow ~60s for first startup.

---

Tab Reference

Group A — Real Data Tools

Tab	Function	APIs Used
A1 — Gray Zones Explorer	Heatmap of biological process × cancer type paper counts; top 5 gaps	PubMed E-utilities
A2 — Understudied Target Finder	Essential genes with high gap index (essentiality / log(papers+1))	OpenTargets GraphQL, PubMed, ClinicalTrials.gov v2
A3 — Real Variant Lookup	ClinVar classification + gnomAD allele frequency for any HGVS variant	ClinVar E-utilities, gnomAD GraphQL
A4 — Literature Gap Finder	Papers/year chart with gap detection (zero and low-activity years)	PubMed E-utilities
A5 — Druggable Orphans	Essential cancer genes with no approved drug and no active trial	OpenTargets GraphQL, ClinicalTrials.gov v2
A6 — Research Assistant	RAG chatbot indexed on 20 curated papers; confidence-flagged answers	sentence-transformers + FAISS (local)

Group B — Learning Sandbox ⚠️ SIMULATED

Tab	Function	Model
B1 — miRNA Explorer	Predicted miRNA binding energy + expression in BRCA1/BRCA2/TP53-mutant tumors	Curated lookup table
B2 — siRNA Targets	siRNA efficacy + off-target risk for LUAD/BRCA/COAD	Curated efficacy estimates
B3 — LNP Corona	Protein corona composition from formulation sliders (PEG, ionizable lipid, size)	Langmuir adsorption model
B4 — Flow Corona	Vroman effect kinetics (competitive albumin/ApoE adsorption)	Competitive Langmuir ODE
B5 — Variant Concepts	ACMG/AMP classification criteria and codes by tier	ACMG 2015 rule set

Shared — Lab Journal (sidebar)

• Auto-logs every tab run with timestamp, action, and result summary
• Manual note field for researcher observations
• Exports to lab_journal.csv
• Click Refresh Journal to view last 20 entries

---

Supported Cancer Types

Code	Full Name	EFO ID
GBM	Glioblastoma multiforme	EFO_0000519
PDAC	Pancreatic ductal adenocarcinoma	EFO_0002618
SCLC	Small cell lung cancer	EFO_0000702
UVM	Uveal melanoma	EFO_0004339
DIPG	Diffuse intrinsic pontine glioma	EFO_0009708
ACC	Adrenocortical carcinoma	EFO_0003060
MCC	Merkel cell carcinoma	EFO_0005558
PCNSL	Primary CNS lymphoma	EFO_0005543
Pediatric AML	Pediatric acute myeloid leukemia	EFO_0000222

---

Biological Processes Screened (Tab A1)

autophagy · ferroptosis · protein corona · RNA splicing · phase separation · m6A · circRNA · synthetic lethality · immune exclusion · enhancer hijacking · lncRNA regulation · metabolic reprogramming · exosome biogenesis · senescence · mitophagy · liquid-liquid phase separation · cryptic splicing · proteostasis · redox biology · translation regulation

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RAG Chatbot Details (Tab A6)

• Model: sentence-transformers/all-MiniLM-L6-v2 (80 MB, CPU-only, no GPU needed)
• Index: FAISS IndexFlatIP with L2-normalized embeddings (cosine similarity)
• Corpus: 20 curated paper abstracts on LNP delivery, protein corona, cancer variants, liquid biopsy
• Confidence flags:
  • 🟢 HIGH — retrieval score ≥ 0.55, ≥ 2 matching papers
  • 🟡 MEDIUM — score 0.35–0.55
  • 🔴 SPECULATIVE — score < 0.35
• Out-of-scope: Returns explicit "not in indexed papers" message — never fabricates

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Caching & Rate Limiting

• All API responses cached in ./cache/ as JSON files (24h TTL)
• PubMed: time.sleep(0.34) between requests (≤3 req/sec, NCBI policy)
• All API calls wrapped in try/except → returns "Data unavailable" on failure, never fake data
• Cache can be cleared by deleting ./cache/ directory

---

Data Attribution

Every result panel displays a source note:

Source: [API name] | Date: YYYY-MM-DD

Full API documentation: see data_sources.md

---

Technical Notes

DepMap Essentiality Scores

Per DepMap convention: negative scores = essential genes (knockout kills cells). The app inverts scores before display: essentiality_displayed = -raw_score so that positive values = more essential (intuitive direction). Gap index = essentiality_inverted / log(papers + 1)

Variant Lookup Policy

Tab A3 strictly follows a no-hallucination policy:

• If a variant is not found in ClinVar → displays: "Not in database. Do not interpret."
• If gnomAD API fails → displays: "Data unavailable — API error."
• Never infers, guesses, or extrapolates variant classifications

SIMULATED Data Policy

All Group B tabs display a prominent ⚠️ SIMULATED banner. Simulated results must not be used for:

• Clinical decision-making
• Publication without independent experimental validation
• Drug development or patient care

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Dependencies

Package	Version	Purpose
gradio	≥4.20.0	UI framework
numpy	≥1.24.0	Numerical computing
pandas	≥2.0.0	Data tables
matplotlib	≥3.7.0	Visualizations
Pillow	≥10.0.0	Image handling
requests	≥2.31.0	HTTP API calls
sentence-transformers	≥2.6.0	RAG embeddings
faiss-cpu	≥1.7.4	Vector similarity search
torch	≥2.0.0	sentence-transformers backend

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License

Research and educational use. All real-data results sourced from public APIs (PubMed, OpenTargets, ClinVar, gnomAD, ClinicalTrials.gov) under their respective open-access licenses. See data_sources.md for details.

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Citation

Kolisnyk O. K R&D Lab — Cancer Research Suite. 2026.
GitHub: github.com/TEZv/K-RnD-Lab-PHYLO-DEMO_03-2026
ORCID: 0009-0003-5780-2290