Brain Organoid Developmental Clock Alignment with LangChain and Claude 4 Opus
NIH research demonstrates that brain organoid maturation follows a predictable, lifelike developmental clock governed by gene expression cascades. In this challenge, developers will construct a bioinformatics pipeline using LangChain stateful graphs (LangGraph) and Claude 4 Opus to process single-cell RNA sequencing (scRNA-seq) gene counts. The agent will align organoid developmental ages against real human fetal cortical reference datasets using Scanpy and AnnData integrations.
What you are building
The core problem, expected build, and operating context for this challenge.
Align single-cell brain organoid transcriptomics with human fetal brain clocks using LangChain and Claude 4 Opus.
How work is evaluated
Evaluates the accuracy of organoid age estimation and trajectory alignment against human fetal brain baselines.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
expression_keys_check
Verify presence of gestational age and marker gene classifications
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
gestational_age_mae
Mean Absolute Error in weeks compared to ground-truth developmental clock • target: 0.5 • range: 0-10
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Construct a LangChain and LangGraph workflow for bioinformatics execution
Process AnnData (.h5ad) single-cell gene expression datasets using Scanpy
Leverage Claude 4 Opus for high-accuracy reasoning on cell-type annotation and temporal developmental stages
Implement batch effect remediation and pseudotime developmental clock mapping
Reference links and supporting material
Single-cell RNA sequencing count matrices from human cortical organoids spanning day 30 to day 300 of maturation.
Challenge setup
Evaluates the accuracy of organoid age estimation and trajectory alignment against human fetal brain baselines.
Challenge input
JSON containing normalized marker gene expression levels
LangChain
Mandatory graph framework
Claude 4 Opus
Assigned reasoning engine
Evaluated output
JSON containing estimated_gestational_week (float) and top_marker_genes (list)
- Verify presence of gestational age and marker gene classifications
- Mean Absolute Error in weeks compared to ground-truth developmental clock • target: 0.5 • range: 0-10
- Benchmark: CellClock-Bench
- Gestational Age Mae target: 0.5
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- LangChain · Optional
- LambdaTest · Optional
- Claude 4 Opus · Required
- LangChain · Optional
Evaluation contract
- expression_keys_check · Weight 1
- gestational_age_mae · Weight 1
Metrics
- gestational_age_mae · Target 0.5
Benchmarks
- CellClock-Bench
- biotech
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing normalized marker gene expression levels
Output: JSON containing estimated_gestational_week (float) and top_marker_genes (list)
Execution harness: Python
Evaluation tools
- LangChain · Agent Framework
- Claude 4 Opus · Foundation Model
Recipe freeze marker
No recipe freeze time is recorded.