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+# Experiment Types and Workflows
+
+## Overview
+
+Adaptyv provides multiple experimental assay types for comprehensive protein characterization. Each experiment type has specific applications, workflows, and data outputs.
+
+## Binding Assays
+
+### Description
+
+Measure protein-target interactions using biolayer interferometry (BLI), a label-free technique that monitors biomolecular binding in real-time.
+
+### Use Cases
+
+- Antibody-antigen binding characterization
+- Receptor-ligand interaction analysis
+- Protein-protein interaction studies
+- Affinity maturation screening
+- Epitope binning experiments
+
+### Technology: Biolayer Interferometry (BLI)
+
+BLI measures the interference pattern of reflected light from two surfaces:
+- **Reference layer** - Biosensor tip surface
+- **Biological layer** - Accumulated bound molecules
+
+As molecules bind, the optical thickness increases, causing a wavelength shift proportional to binding.
+
+**Advantages:**
+- Label-free detection
+- Real-time kinetics
+- High-throughput compatible
+- Works in crude samples
+- Minimal sample consumption
+
+### Measured Parameters
+
+**Kinetic constants:**
+- **KD** - Equilibrium dissociation constant (binding affinity)
+- **kon** - Association rate constant (binding speed)
+- **koff** - Dissociation rate constant (unbinding speed)
+
+**Typical ranges:**
+- Strong binders: KD < 1 nM
+- Moderate binders: KD = 1-100 nM
+- Weak binders: KD > 100 nM
+
+### Workflow
+
+1. **Sequence submission** - Provide protein sequences in FASTA format
+2. **Expression** - Proteins expressed in appropriate host system
+3. **Purification** - Automated purification protocols
+4. **BLI assay** - Real-time binding measurements against specified targets
+5. **Analysis** - Kinetic curve fitting and quality assessment
+6. **Results delivery** - Binding parameters with confidence metrics
+
+### Sample Requirements
+
+- Protein sequence (standard amino acid codes)
+- Target specification (from catalog or custom request)
+- Buffer conditions (standard or custom)
+- Expected concentration range (optional, improves assay design)
+
+### Results Format
+
+```json
+{
+  "sequence_id": "antibody_variant_1",
+  "target": "Human PD-L1",
+  "measurements": {
+    "kd": 2.5e-9,
+    "kd_error": 0.3e-9,
+    "kon": 1.8e5,
+    "kon_error": 0.2e5,
+    "koff": 4.5e-4,
+    "koff_error": 0.5e-4
+  },
+  "quality_metrics": {
+    "confidence": "high|medium|low",
+    "r_squared": 0.97,
+    "chi_squared": 0.02,
+    "flags": []
+  },
+  "raw_data_url": "https://..."
+}
+```
+
+## Expression Testing
+
+### Description
+
+Quantify protein expression levels in various host systems to assess producibility and optimize sequences for manufacturing.
+
+### Use Cases
+
+- Screening variants for high expression
+- Optimizing codon usage
+- Identifying expression bottlenecks
+- Selecting candidates for scale-up
+- Comparing expression systems
+
+### Host Systems
+
+Available expression platforms:
+- **E. coli** - Rapid, cost-effective, prokaryotic system
+- **Mammalian cells** - Native post-translational modifications
+- **Yeast** - Eukaryotic system with simpler growth requirements
+- **Insect cells** - Alternative eukaryotic platform
+
+### Measured Parameters
+
+- **Total protein yield** (mg/L culture)
+- **Soluble fraction** (percentage)
+- **Purity** (after initial purification)
+- **Expression time course** (optional)
+
+### Workflow
+
+1. **Sequence submission** - Provide protein sequences
+2. **Construct generation** - Cloning into expression vectors
+3. **Expression** - Culture in specified host system
+4. **Quantification** - Protein measurement via multiple methods
+5. **Analysis** - Expression level comparison and ranking
+6. **Results delivery** - Yield data and recommendations
+
+### Results Format
+
+```json
+{
+  "sequence_id": "variant_1",
+  "host_system": "E. coli",
+  "measurements": {
+    "total_yield_mg_per_l": 25.5,
+    "soluble_fraction_percent": 78,
+    "purity_percent": 92
+  },
+  "ranking": {
+    "percentile": 85,
+    "notes": "High expression, good solubility"
+  }
+}
+```
+
+## Thermostability Testing
+
+### Description
+
+Measure protein thermal stability to assess structural integrity, predict shelf-life, and identify stabilizing mutations.
+
+### Use Cases
+
+- Selecting thermally stable variants
+- Formulation development
+- Shelf-life prediction
+- Stability-driven protein engineering
+- Quality control screening
+
+### Measurement Techniques
+
+**Differential Scanning Fluorimetry (DSF):**
+- Monitors protein unfolding via fluorescent dye binding
+- Determines melting temperature (Tm)
+- High-throughput capable
+
+**Circular Dichroism (CD):**
+- Secondary structure analysis
+- Thermal unfolding curves
+- Reversibility assessment
+
+### Measured Parameters
+
+- **Tm** - Melting temperature (midpoint of unfolding)
+- **ΔH** - Enthalpy of unfolding
+- **Aggregation temperature** (Tagg)
+- **Reversibility** - Refolding after heating
+
+### Workflow
+
+1. **Sequence submission** - Provide protein sequences
+2. **Expression and purification** - Standard protocols
+3. **Thermostability assay** - Temperature gradient analysis
+4. **Data analysis** - Curve fitting and parameter extraction
+5. **Results delivery** - Stability metrics with ranking
+
+### Results Format
+
+```json
+{
+  "sequence_id": "variant_1",
+  "measurements": {
+    "tm_celsius": 68.5,
+    "tm_error": 0.5,
+    "tagg_celsius": 72.0,
+    "reversibility_percent": 85
+  },
+  "quality_metrics": {
+    "curve_quality": "excellent",
+    "cooperativity": "two-state"
+  }
+}
+```
+
+## Enzyme Activity Assays
+
+### Description
+
+Measure enzymatic function including substrate turnover, catalytic efficiency, and inhibitor sensitivity.
+
+### Use Cases
+
+- Screening enzyme variants for improved activity
+- Substrate specificity profiling
+- Inhibitor testing
+- pH and temperature optimization
+- Mechanistic studies
+
+### Assay Types
+
+**Continuous assays:**
+- Chromogenic substrates
+- Fluorogenic substrates
+- Real-time monitoring
+
+**Endpoint assays:**
+- HPLC quantification
+- Mass spectrometry
+- Colorimetric detection
+
+### Measured Parameters
+
+**Kinetic parameters:**
+- **kcat** - Turnover number (catalytic rate constant)
+- **KM** - Michaelis constant (substrate affinity)
+- **kcat/KM** - Catalytic efficiency
+- **IC50** - Inhibitor concentration for 50% inhibition
+
+**Activity metrics:**
+- Specific activity (units/mg protein)
+- Relative activity vs. reference
+- Substrate specificity profile
+
+### Workflow
+
+1. **Sequence submission** - Provide enzyme sequences
+2. **Expression and purification** - Optimized for activity retention
+3. **Activity assay** - Substrate turnover measurements
+4. **Kinetic analysis** - Michaelis-Menten fitting
+5. **Results delivery** - Kinetic parameters and rankings
+
+### Results Format
+
+```json
+{
+  "sequence_id": "enzyme_variant_1",
+  "substrate": "substrate_name",
+  "measurements": {
+    "kcat_per_second": 125,
+    "km_micromolar": 45,
+    "kcat_km": 2.8,
+    "specific_activity": 180
+  },
+  "quality_metrics": {
+    "confidence": "high",
+    "r_squared": 0.99
+  },
+  "ranking": {
+    "relative_activity": 1.8,
+    "improvement_vs_wildtype": "80%"
+  }
+}
+```
+
+## Experiment Design Best Practices
+
+### Sequence Submission
+
+1. **Use clear identifiers** - Name sequences descriptively
+2. **Include controls** - Submit wild-type or reference sequences
+3. **Batch similar variants** - Group related sequences in single submission
+4. **Validate sequences** - Check for errors before submission
+
+### Sample Size
+
+- **Pilot studies** - 5-10 sequences to test feasibility
+- **Library screening** - 50-500 sequences for variant exploration
+- **Focused optimization** - 10-50 sequences for fine-tuning
+- **Large-scale campaigns** - 500+ sequences for ML-driven design
+
+### Quality Control
+
+Adaptyv includes automated QC steps:
+- Expression verification before assay
+- Replicate measurements for reliability
+- Positive/negative controls in each batch
+- Statistical validation of results
+
+### Timeline Expectations
+
+**Standard turnaround:** ~21 days from submission to results
+
+**Timeline breakdown:**
+- Construct generation: 3-5 days
+- Expression: 5-7 days
+- Purification: 2-3 days
+- Assay execution: 3-5 days
+- Analysis and QC: 2-3 days
+
+**Factors affecting timeline:**
+- Custom targets (add 1-2 weeks)
+- Novel assay development (add 2-4 weeks)
+- Large batch sizes (may add 1 week)
+
+### Cost Optimization
+
+1. **Batch submissions** - Lower per-sequence cost
+2. **Standard targets** - Catalog antigens are faster/cheaper
+3. **Standard conditions** - Custom buffers add cost
+4. **Computational pre-filtering** - Submit only promising candidates
+
+## Combining Experiment Types
+
+For comprehensive protein characterization, combine multiple assays:
+
+**Therapeutic antibody development:**
+1. Binding assay → Identify high-affinity binders
+2. Expression testing → Select manufacturable candidates
+3. Thermostability → Ensure formulation stability
+
+**Enzyme engineering:**
+1. Activity assay → Screen for improved catalysis
+2. Expression testing → Ensure producibility
+3. Thermostability → Validate industrial robustness
+
+**Sequential vs. Parallel:**
+- **Sequential** - Use results from early assays to filter candidates
+- **Parallel** - Run all assays simultaneously for faster results
+
+## Data Integration
+
+Results integrate with computational workflows:
+
+1. **Download raw data** via API
+2. **Parse results** into standardized format
+3. **Feed into ML models** for next-round design
+4. **Track experiments** with metadata tags
+5. **Visualize trends** across design iterations
+
+## Support and Troubleshooting
+
+**Common issues:**
+- Low expression → Consider sequence optimization (see protein_optimization.md)
+- Poor binding → Verify target specification and expected range
+- Variable results → Check sequence quality and controls
+- Incomplete data → Contact support with experiment ID
+
+**Getting help:**
+- Email: support@adaptyvbio.com
+- Include experiment ID and specific question
+- Provide context (design goals, expected results)
+- Response time: <24 hours for active experiments