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README.md

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-# Cancer@Home v2
-
-A distributed computing platform for cancer genomics research, combining BOINC distributed computing, GDC cancer data analysis, sequence processing (FASTQ/BLAST), and Neo4j graph visualization.
-
-## 🚀 Quick Start (5 minutes)
-
-### Prerequisites
-- Python 3.8+
-- Docker Desktop
-- 8GB RAM minimum
-
-### Installation
-
-1. **Clone and setup**
-```bash
-cd CancerAtHome2
-python -m venv venv
-venv\Scripts\activate  # Windows
-pip install -r requirements.txt
-```
-
-2. **Start Neo4j Database**
-```bash
-docker-compose up -d
-```
-
-3. **Run the application**
-```bash
-python run.py
-```
-
-4. **Open your browser**
-- Application: http://localhost:5000
-- Neo4j Browser: http://localhost:7474 (username: neo4j, password: cancer123)
-
-## 🎯 Features
-
-### 1. **Distributed Computing (BOINC Integration)**
-- Submit cancer research computational tasks
-- Monitor distributed workload processing
-- Real-time task status tracking
-
-### 2. **GDC Data Integration**
-- Download cancer genomics data from GDC Portal
-- Support for various cancer types (TCGA, TARGET projects)
-- Automatic data parsing and normalization
-
-### 3. **Sequence Analysis Pipeline**
-- FASTQ file processing
-- BLAST sequence alignment
-- Variant calling and annotation
-
-### 4. **Neo4j Graph Database**
-- Graph-based cancer data modeling
-- Relationships: Gene → Mutation → Patient → Cancer Type
-- Interactive graph visualization
-
-### 5. **GraphQL API**
-- Query cancer data flexibly
-- Filter by gene, mutation, patient cohort
-- Aggregate statistics
-
-### 6. **Interactive Dashboard**
-- Real-time data visualization
-- Network graphs for gene interactions
-- Mutation frequency charts
-- Patient cohort analysis
-
-## 📊 Architecture
-
-```
-Cancer@Home v2
-│
-├── Frontend (React + D3.js)
-│   ├── Dashboard
-│   ├── Neo4j Visualization
-│   └── Task Monitor
-│
-├── Backend (FastAPI)
-│   ├── REST API
-│   ├── GraphQL Endpoint
-│   └── WebSocket (real-time updates)
-│
-├── Data Layer
-│   ├── Neo4j (Graph Database)
-│   ├── BOINC Client
-│   └── GDC API Client
-│
-└── Analysis Pipeline
-    ├── FASTQ Parser
-    ├── BLAST Wrapper
-    └── Variant Annotator
-```
-
-## 🗂️ Project Structure
-
-```
-CancerAtHome2/
-├── backend/
-│   ├── api/              # FastAPI routes
-│   ├── boinc/            # BOINC integration
-│   ├── gdc/              # GDC data fetcher
-│   ├── neo4j/            # Neo4j database layer
-│   ├── pipeline/         # Bioinformatics pipeline
-│   └── graphql/          # GraphQL schema
-├── frontend/
-│   ├── public/
-│   └── src/
-│       ├── components/   # React components
-│       ├── views/        # Page views
-│       └── api/          # API client
-├── data/                 # Downloaded datasets
-├── docker-compose.yml    # Neo4j container
-├── requirements.txt      # Python dependencies
-└── run.py               # Main entry point
-```
-
-## 🧬 Data Flow
-
-1. **Data Ingestion**: Download cancer genomics data from GDC Portal
-2. **Processing**: Run FASTQ/BLAST analysis on distributed BOINC network
-3. **Storage**: Store results in Neo4j graph database
-4. **Visualization**: Query and visualize via web dashboard
-
-## 🔧 Configuration
-
-Edit `config.yml` to customize:
-- Neo4j connection settings
-- GDC API parameters
-- BOINC project URL
-- Analysis pipeline options
-
-## 📖 Usage Examples
-
-### Query Mutations by Gene
-```graphql
-query {
-  mutations(gene: "TP53") {
-    id
-    position
-    consequence
-    patients {
-      cancerType
-      stage
-    }
-  }
-}
-```
-
-### Submit Analysis Task
-```python
-from backend.boinc import BOINCClient
-
-client = BOINCClient()
-task_id = client.submit_task(
-    workunit_type="variant_calling",
-    input_file="sample.fastq"
-)
-```
-
-## 🤝 Inspired By
-
-- [Cancer@Home v1](https://www.herox.com/DCx/round/516/entry/23285) - Distributed cancer research
-- [Neo4j Cancer Visualization](https://medium.com/neo4j/visualize-cancer-1c80a95f5bb4) - Graph-based cancer data modeling
-
-## 📄 License
-
-MIT License
-
-## 🛟 Support
-
-For issues or questions, please open a GitHub issue.
+---
+license: mit
+language:
+- en
+metrics:
+- accuracy
+- bleu
+- bleurt
+---
+# Cancer@Home v2
+
+A distributed computing platform for cancer genomics research, combining BOINC distributed computing, GDC cancer data analysis, sequence processing (FASTQ/BLAST), and Neo4j graph visualization.
+
+## 🚀 Quick Start (5 minutes)
+
+### Prerequisites
+- Python 3.8+
+- Docker Desktop
+- 8GB RAM minimum
+
+### Installation
+
+1. **Clone and setup**
+```bash
+cd CancerAtHome2
+python -m venv venv
+venv\Scripts\activate  # Windows
+pip install -r requirements.txt
+```
+
+2. **Start Neo4j Database**
+```bash
+docker-compose up -d
+```
+
+3. **Run the application**
+```bash
+python run.py
+```
+
+4. **Open your browser**
+- Application: http://localhost:5000
+- Neo4j Browser: http://localhost:7474 (username: neo4j, password: cancer123)
+
+## 🎯 Features
+
+### 1. **Distributed Computing (BOINC Integration)**
+- Submit cancer research computational tasks
+- Monitor distributed workload processing
+- Real-time task status tracking
+
+### 2. **GDC Data Integration**
+- Download cancer genomics data from GDC Portal
+- Support for various cancer types (TCGA, TARGET projects)
+- Automatic data parsing and normalization
+
+### 3. **Sequence Analysis Pipeline**
+- FASTQ file processing
+- BLAST sequence alignment
+- Variant calling and annotation
+
+### 4. **Neo4j Graph Database**
+- Graph-based cancer data modeling
+- Relationships: Gene → Mutation → Patient → Cancer Type
+- Interactive graph visualization
+
+### 5. **GraphQL API**
+- Query cancer data flexibly
+- Filter by gene, mutation, patient cohort
+- Aggregate statistics
+
+### 6. **Interactive Dashboard**
+- Real-time data visualization
+- Network graphs for gene interactions
+- Mutation frequency charts
+- Patient cohort analysis
+
+## 📊 Architecture
+
+```
+Cancer@Home v2
+│
+├── Frontend (React + D3.js)
+│   ├── Dashboard
+│   ├── Neo4j Visualization
+│   └── Task Monitor
+│
+├── Backend (FastAPI)
+│   ├── REST API
+│   ├── GraphQL Endpoint
+│   └── WebSocket (real-time updates)
+│
+├── Data Layer
+│   ├── Neo4j (Graph Database)
+│   ├── BOINC Client
+│   └── GDC API Client
+│
+└── Analysis Pipeline
+    ├── FASTQ Parser
+    ├── BLAST Wrapper
+    └── Variant Annotator
+```
+
+## 🗂️ Project Structure
+
+```
+CancerAtHome2/
+├── backend/
+│   ├── api/              # FastAPI routes
+│   ├── boinc/            # BOINC integration
+│   ├── gdc/              # GDC data fetcher
+│   ├── neo4j/            # Neo4j database layer
+│   ├── pipeline/         # Bioinformatics pipeline
+│   └── graphql/          # GraphQL schema
+├── frontend/
+│   ├── public/
+│   └── src/
+│       ├── components/   # React components
+│       ├── views/        # Page views
+│       └── api/          # API client
+├── data/                 # Downloaded datasets
+├── docker-compose.yml    # Neo4j container
+├── requirements.txt      # Python dependencies
+└── run.py               # Main entry point
+```
+
+## 🧬 Data Flow
+
+1. **Data Ingestion**: Download cancer genomics data from GDC Portal
+2. **Processing**: Run FASTQ/BLAST analysis on distributed BOINC network
+3. **Storage**: Store results in Neo4j graph database
+4. **Visualization**: Query and visualize via web dashboard
+
+## 🔧 Configuration
+
+Edit `config.yml` to customize:
+- Neo4j connection settings
+- GDC API parameters
+- BOINC project URL
+- Analysis pipeline options
+
+## 📖 Usage Examples
+
+### Query Mutations by Gene
+```graphql
+query {
+  mutations(gene: "TP53") {
+    id
+    position
+    consequence
+    patients {
+      cancerType
+      stage
+    }
+  }
+}
+```
+
+### Submit Analysis Task
+```python
+from backend.boinc import BOINCClient
+
+client = BOINCClient()
+task_id = client.submit_task(
+    workunit_type="variant_calling",
+    input_file="sample.fastq"
+)
+```
+
+## 🤝 Inspired By
+
+- [Cancer@Home v1](https://www.herox.com/DCx/round/516/entry/23285) - Distributed cancer research
+- [Neo4j Cancer Visualization](https://medium.com/neo4j/visualize-cancer-1c80a95f5bb4) - Graph-based cancer data modeling
+
+## 📄 License
+
+MIT License
+
+## 🛟 Support
+
+For issues or questions, please open a Huggingface or GitHub issue.